JV
J.H. Vroon
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9 records found
1
Recent technological advancements are revolutionizing last-mile package delivery, with autonomous delivery vehicles (ADVs) emerging as a sustainable alternative. These small ground vehicles autonomously navigate pavements, aiming to operate seamlessly in pedestrian-rich environments without any human intervention. The goal of this project is to design a concept of an autonomous delivery vehicle that portrays predictable behaviour for pedestrians.
Extensive research involving literature analysis, interviews, and observational studies unveiled the challenges that current ADVs are facing, including unpredictable behaviour and distrust. The absence of predictability has a big impact on effective on-road communication, and it potentially leads to unsafe traffic interactions. A viable solution lies in communicating the ADV's driving intent. This study delves into the nuances of intent communication in pedestrian environments, and identifies intent signals that are predominantly communicated through body language. The objective is to replicate human-like signals in the behaviour of ADVs, to ensure an intuitive understanding of such cues from previous traffic experiences.
Focusing on designing predictability through intent communication via body language, a test exploration is conducted, testing multiple different prototypes. Iterative trials resulted in interesting insights and eventually lead to the most promising intent signal – the "Looking" scenario. This intent signal is inspired by a head-turning or someone looking into the desired walking direction. Participants recognised this signal, facilitating an intuitive understanding of the meaning of the signal.
The evaluation test confirmed the intent signal's positive effect on enhancing pedestrians' feelings of safety, trust, and comfort during an ADV interaction. These increased feelings of safety, trust and comfortability came from the fact that they were able to predict the movements of the ADV and because they felt "seen". The robot reacted to the participants by showing its intent, this reaction gave participants the perception that the ADV has indeed detected them and therefore won't collide with them. Consequently, it is recommended to integrate intent communication into ADV designs to ensure safer and more harmonious ADV-pedestrian interactions.
Three design guidelines are formulated based on the insights from the exploration phase. The three guidelines emphasize the interpretation, visibility, and relevance of intent signals. The conceptual ADV design presented in this project, aligns with these guidelines. The intent signal in the design concept of the ADV makes their behaviour more predictable, gives people a sense of control because they feel detected, which both leads to an increase in safety, trust, and comfortability. Although the intent signal shows great promise in creating a safer and more comfortable traffic interaction between ADVs and pedestrians, additional research is needed to fully understand the impact of integrating this intent signal.
...
Extensive research involving literature analysis, interviews, and observational studies unveiled the challenges that current ADVs are facing, including unpredictable behaviour and distrust. The absence of predictability has a big impact on effective on-road communication, and it potentially leads to unsafe traffic interactions. A viable solution lies in communicating the ADV's driving intent. This study delves into the nuances of intent communication in pedestrian environments, and identifies intent signals that are predominantly communicated through body language. The objective is to replicate human-like signals in the behaviour of ADVs, to ensure an intuitive understanding of such cues from previous traffic experiences.
Focusing on designing predictability through intent communication via body language, a test exploration is conducted, testing multiple different prototypes. Iterative trials resulted in interesting insights and eventually lead to the most promising intent signal – the "Looking" scenario. This intent signal is inspired by a head-turning or someone looking into the desired walking direction. Participants recognised this signal, facilitating an intuitive understanding of the meaning of the signal.
The evaluation test confirmed the intent signal's positive effect on enhancing pedestrians' feelings of safety, trust, and comfort during an ADV interaction. These increased feelings of safety, trust and comfortability came from the fact that they were able to predict the movements of the ADV and because they felt "seen". The robot reacted to the participants by showing its intent, this reaction gave participants the perception that the ADV has indeed detected them and therefore won't collide with them. Consequently, it is recommended to integrate intent communication into ADV designs to ensure safer and more harmonious ADV-pedestrian interactions.
Three design guidelines are formulated based on the insights from the exploration phase. The three guidelines emphasize the interpretation, visibility, and relevance of intent signals. The conceptual ADV design presented in this project, aligns with these guidelines. The intent signal in the design concept of the ADV makes their behaviour more predictable, gives people a sense of control because they feel detected, which both leads to an increase in safety, trust, and comfortability. Although the intent signal shows great promise in creating a safer and more comfortable traffic interaction between ADVs and pedestrians, additional research is needed to fully understand the impact of integrating this intent signal.
...
Recent technological advancements are revolutionizing last-mile package delivery, with autonomous delivery vehicles (ADVs) emerging as a sustainable alternative. These small ground vehicles autonomously navigate pavements, aiming to operate seamlessly in pedestrian-rich environments without any human intervention. The goal of this project is to design a concept of an autonomous delivery vehicle that portrays predictable behaviour for pedestrians.
Extensive research involving literature analysis, interviews, and observational studies unveiled the challenges that current ADVs are facing, including unpredictable behaviour and distrust. The absence of predictability has a big impact on effective on-road communication, and it potentially leads to unsafe traffic interactions. A viable solution lies in communicating the ADV's driving intent. This study delves into the nuances of intent communication in pedestrian environments, and identifies intent signals that are predominantly communicated through body language. The objective is to replicate human-like signals in the behaviour of ADVs, to ensure an intuitive understanding of such cues from previous traffic experiences.
Focusing on designing predictability through intent communication via body language, a test exploration is conducted, testing multiple different prototypes. Iterative trials resulted in interesting insights and eventually lead to the most promising intent signal – the "Looking" scenario. This intent signal is inspired by a head-turning or someone looking into the desired walking direction. Participants recognised this signal, facilitating an intuitive understanding of the meaning of the signal.
The evaluation test confirmed the intent signal's positive effect on enhancing pedestrians' feelings of safety, trust, and comfort during an ADV interaction. These increased feelings of safety, trust and comfortability came from the fact that they were able to predict the movements of the ADV and because they felt "seen". The robot reacted to the participants by showing its intent, this reaction gave participants the perception that the ADV has indeed detected them and therefore won't collide with them. Consequently, it is recommended to integrate intent communication into ADV designs to ensure safer and more harmonious ADV-pedestrian interactions.
Three design guidelines are formulated based on the insights from the exploration phase. The three guidelines emphasize the interpretation, visibility, and relevance of intent signals. The conceptual ADV design presented in this project, aligns with these guidelines. The intent signal in the design concept of the ADV makes their behaviour more predictable, gives people a sense of control because they feel detected, which both leads to an increase in safety, trust, and comfortability. Although the intent signal shows great promise in creating a safer and more comfortable traffic interaction between ADVs and pedestrians, additional research is needed to fully understand the impact of integrating this intent signal.
Extensive research involving literature analysis, interviews, and observational studies unveiled the challenges that current ADVs are facing, including unpredictable behaviour and distrust. The absence of predictability has a big impact on effective on-road communication, and it potentially leads to unsafe traffic interactions. A viable solution lies in communicating the ADV's driving intent. This study delves into the nuances of intent communication in pedestrian environments, and identifies intent signals that are predominantly communicated through body language. The objective is to replicate human-like signals in the behaviour of ADVs, to ensure an intuitive understanding of such cues from previous traffic experiences.
Focusing on designing predictability through intent communication via body language, a test exploration is conducted, testing multiple different prototypes. Iterative trials resulted in interesting insights and eventually lead to the most promising intent signal – the "Looking" scenario. This intent signal is inspired by a head-turning or someone looking into the desired walking direction. Participants recognised this signal, facilitating an intuitive understanding of the meaning of the signal.
The evaluation test confirmed the intent signal's positive effect on enhancing pedestrians' feelings of safety, trust, and comfort during an ADV interaction. These increased feelings of safety, trust and comfortability came from the fact that they were able to predict the movements of the ADV and because they felt "seen". The robot reacted to the participants by showing its intent, this reaction gave participants the perception that the ADV has indeed detected them and therefore won't collide with them. Consequently, it is recommended to integrate intent communication into ADV designs to ensure safer and more harmonious ADV-pedestrian interactions.
Three design guidelines are formulated based on the insights from the exploration phase. The three guidelines emphasize the interpretation, visibility, and relevance of intent signals. The conceptual ADV design presented in this project, aligns with these guidelines. The intent signal in the design concept of the ADV makes their behaviour more predictable, gives people a sense of control because they feel detected, which both leads to an increase in safety, trust, and comfortability. Although the intent signal shows great promise in creating a safer and more comfortable traffic interaction between ADVs and pedestrians, additional research is needed to fully understand the impact of integrating this intent signal.
Stitched Strain Sensors
Supporting At-Home Rehabilitation Exercises
The process of physical rehabilitation in most cases consists of visits to a physical therapist and exercises the patient is expected to perform at home. To increase or maintain strength or flexibility these exercises need to be performed regularly. Practice teaches us that not all patients succeed here. In this project, we look into what is keeping them from succeeding and how we can support this process.
In literature, four categories of barriers are described, from which the psychological barriers are most interesting to investigate further within this project. Motivation plays a big part within this category.
The Fogg model gives structure to the different components of motivation and different factors influencing the execution of preferred behavior. It shows us triggers will fail if motivation is low or the task takes too much effort to complete.
In a lot of the cases, the intention to complete the exercises is present with the client, but the behavior does not reflect this intention. The intention-behavior gap can be bridged the same way the fogg model suggests triggers to be efficient, by motivating the user or making the task take less effort.
By providing support during the exercise - providing both motivation and decreasing effort - and giving the patient the opportunity to track their progress after doing the exercises for a longer amount of time we can increase the exercise adherence.
To provide support, we need to gather data on the movements that are made during the exercise. We developed a textile stitched strain sensor that tracks the angle of a joint. The sensor has conductive thread stitched in a tight zigzag pattern onto Kinesio tape. Since the tape is adhered to the skin, the sensor experiences minimal hysteresis.
Using the data gathered by the stitched strain sensor, we tested giving back different kinds of feedback using two different actuators. We found that giving the test subjects more precise data on their movement made them more accurate, but at the same time, made them experience their movement as less accurate. This on the one hand, gave them more motivation to improve, but also made them less confident in performing the exercise.
The project proves that using the real time data gathered by the stitched strain sensor can add to better executing of on exercise and has potential to with that data also contribute to long term exercise-adherence.
...
In literature, four categories of barriers are described, from which the psychological barriers are most interesting to investigate further within this project. Motivation plays a big part within this category.
The Fogg model gives structure to the different components of motivation and different factors influencing the execution of preferred behavior. It shows us triggers will fail if motivation is low or the task takes too much effort to complete.
In a lot of the cases, the intention to complete the exercises is present with the client, but the behavior does not reflect this intention. The intention-behavior gap can be bridged the same way the fogg model suggests triggers to be efficient, by motivating the user or making the task take less effort.
By providing support during the exercise - providing both motivation and decreasing effort - and giving the patient the opportunity to track their progress after doing the exercises for a longer amount of time we can increase the exercise adherence.
To provide support, we need to gather data on the movements that are made during the exercise. We developed a textile stitched strain sensor that tracks the angle of a joint. The sensor has conductive thread stitched in a tight zigzag pattern onto Kinesio tape. Since the tape is adhered to the skin, the sensor experiences minimal hysteresis.
Using the data gathered by the stitched strain sensor, we tested giving back different kinds of feedback using two different actuators. We found that giving the test subjects more precise data on their movement made them more accurate, but at the same time, made them experience their movement as less accurate. This on the one hand, gave them more motivation to improve, but also made them less confident in performing the exercise.
The project proves that using the real time data gathered by the stitched strain sensor can add to better executing of on exercise and has potential to with that data also contribute to long term exercise-adherence.
...
The process of physical rehabilitation in most cases consists of visits to a physical therapist and exercises the patient is expected to perform at home. To increase or maintain strength or flexibility these exercises need to be performed regularly. Practice teaches us that not all patients succeed here. In this project, we look into what is keeping them from succeeding and how we can support this process.
In literature, four categories of barriers are described, from which the psychological barriers are most interesting to investigate further within this project. Motivation plays a big part within this category.
The Fogg model gives structure to the different components of motivation and different factors influencing the execution of preferred behavior. It shows us triggers will fail if motivation is low or the task takes too much effort to complete.
In a lot of the cases, the intention to complete the exercises is present with the client, but the behavior does not reflect this intention. The intention-behavior gap can be bridged the same way the fogg model suggests triggers to be efficient, by motivating the user or making the task take less effort.
By providing support during the exercise - providing both motivation and decreasing effort - and giving the patient the opportunity to track their progress after doing the exercises for a longer amount of time we can increase the exercise adherence.
To provide support, we need to gather data on the movements that are made during the exercise. We developed a textile stitched strain sensor that tracks the angle of a joint. The sensor has conductive thread stitched in a tight zigzag pattern onto Kinesio tape. Since the tape is adhered to the skin, the sensor experiences minimal hysteresis.
Using the data gathered by the stitched strain sensor, we tested giving back different kinds of feedback using two different actuators. We found that giving the test subjects more precise data on their movement made them more accurate, but at the same time, made them experience their movement as less accurate. This on the one hand, gave them more motivation to improve, but also made them less confident in performing the exercise.
The project proves that using the real time data gathered by the stitched strain sensor can add to better executing of on exercise and has potential to with that data also contribute to long term exercise-adherence.
In literature, four categories of barriers are described, from which the psychological barriers are most interesting to investigate further within this project. Motivation plays a big part within this category.
The Fogg model gives structure to the different components of motivation and different factors influencing the execution of preferred behavior. It shows us triggers will fail if motivation is low or the task takes too much effort to complete.
In a lot of the cases, the intention to complete the exercises is present with the client, but the behavior does not reflect this intention. The intention-behavior gap can be bridged the same way the fogg model suggests triggers to be efficient, by motivating the user or making the task take less effort.
By providing support during the exercise - providing both motivation and decreasing effort - and giving the patient the opportunity to track their progress after doing the exercises for a longer amount of time we can increase the exercise adherence.
To provide support, we need to gather data on the movements that are made during the exercise. We developed a textile stitched strain sensor that tracks the angle of a joint. The sensor has conductive thread stitched in a tight zigzag pattern onto Kinesio tape. Since the tape is adhered to the skin, the sensor experiences minimal hysteresis.
Using the data gathered by the stitched strain sensor, we tested giving back different kinds of feedback using two different actuators. We found that giving the test subjects more precise data on their movement made them more accurate, but at the same time, made them experience their movement as less accurate. This on the one hand, gave them more motivation to improve, but also made them less confident in performing the exercise.
The project proves that using the real time data gathered by the stitched strain sensor can add to better executing of on exercise and has potential to with that data also contribute to long term exercise-adherence.
As current cleaning targets are not achieved, Amsterdam requested to explore the potential for robots to contribute to a cleaner city. This thesis focused on exploring how a robot could contribute. A contextual analysis, reviewing literature and municipal documents, showed an increasing need for improved waste management efficiency in response to Amsterdam’s growth, increasing tourism and sustainability goals. However, increasing labour shortages and demographic ageing make it difficult to rely solely on additional human labour in the coming years.
To further analyse the context, employees of department Schoon were accompanied and interviewed. Six key values were identified contributing to job satisfaction - safeguarding these is crucial for successful robot implementation, including freedom and dislike of heavy work. Challenges were also identified, including labour shortages and reduced efficiency.
To determine where a robot could add value, three main waste problems in Amsterdam were identified and analysed. Inefficient waste management and littering behaviour were often the cause. To understand this behaviour, key influencing factors were identified and used in the analysis and thesis.
Furthermore, by analysing key factors of waste management behaviour, it was found that a cleaning robot can potentially trigger motivators for littering behaviour, suggesting that the robot's task influences waste management behaviour. Furthermore, when identifying factors influencing HRI, it was found that rewarding interactions can motivate proper behaviour, suggesting that robots can contribute to a cleaner environment without having to clean.
Based on the findings, specific requirements and a design vision for the robot were established, emphasising promoting proper waste management behaviour, ownership and waste management efficiency. To communicate the vision to the municipality, two concepts were developed, the Mobile Robot Bin and Mobile Robot Container. The Robot Bin aims to motivate proper behaviour through rewarding interactions and to increase waste collection efficiency. To align with Amsterdam's identity and raise awareness, the appearance will be created in collaboration with local artists.
The Robot Container focuses on providing waste disposal options at will in the city centre, optimising waste management efficiency and reducing littering behaviour, as the current policy allows residents to place waste outside twice a week. The concept reduces the physical burden on employees by eliminating the need to collect waste from the street and minimises the need for heavy waste trucks in the centre.
To assess the concepts’ value and feasibility in contributing to a cleaner Amsterdam, stakeholders from the municipality of Amsterdam, department Schoon and AMS Institute evaluated them. Both received positive feedback, with the Robot Container being identified as the most promising solution for achieving a cleaner Amsterdam. However, challenges such as vandalism need to be addressed before implementation. Nevertheless, stakeholders were enthusiastic and asked about implementation activities. A roadmap outlining these activities was developed and evaluated by the AMS expert. However, further research is needed to develop and implement the robots to achieve a cleaner Amsterdam.
...
To further analyse the context, employees of department Schoon were accompanied and interviewed. Six key values were identified contributing to job satisfaction - safeguarding these is crucial for successful robot implementation, including freedom and dislike of heavy work. Challenges were also identified, including labour shortages and reduced efficiency.
To determine where a robot could add value, three main waste problems in Amsterdam were identified and analysed. Inefficient waste management and littering behaviour were often the cause. To understand this behaviour, key influencing factors were identified and used in the analysis and thesis.
Furthermore, by analysing key factors of waste management behaviour, it was found that a cleaning robot can potentially trigger motivators for littering behaviour, suggesting that the robot's task influences waste management behaviour. Furthermore, when identifying factors influencing HRI, it was found that rewarding interactions can motivate proper behaviour, suggesting that robots can contribute to a cleaner environment without having to clean.
Based on the findings, specific requirements and a design vision for the robot were established, emphasising promoting proper waste management behaviour, ownership and waste management efficiency. To communicate the vision to the municipality, two concepts were developed, the Mobile Robot Bin and Mobile Robot Container. The Robot Bin aims to motivate proper behaviour through rewarding interactions and to increase waste collection efficiency. To align with Amsterdam's identity and raise awareness, the appearance will be created in collaboration with local artists.
The Robot Container focuses on providing waste disposal options at will in the city centre, optimising waste management efficiency and reducing littering behaviour, as the current policy allows residents to place waste outside twice a week. The concept reduces the physical burden on employees by eliminating the need to collect waste from the street and minimises the need for heavy waste trucks in the centre.
To assess the concepts’ value and feasibility in contributing to a cleaner Amsterdam, stakeholders from the municipality of Amsterdam, department Schoon and AMS Institute evaluated them. Both received positive feedback, with the Robot Container being identified as the most promising solution for achieving a cleaner Amsterdam. However, challenges such as vandalism need to be addressed before implementation. Nevertheless, stakeholders were enthusiastic and asked about implementation activities. A roadmap outlining these activities was developed and evaluated by the AMS expert. However, further research is needed to develop and implement the robots to achieve a cleaner Amsterdam.
...
As current cleaning targets are not achieved, Amsterdam requested to explore the potential for robots to contribute to a cleaner city. This thesis focused on exploring how a robot could contribute. A contextual analysis, reviewing literature and municipal documents, showed an increasing need for improved waste management efficiency in response to Amsterdam’s growth, increasing tourism and sustainability goals. However, increasing labour shortages and demographic ageing make it difficult to rely solely on additional human labour in the coming years.
To further analyse the context, employees of department Schoon were accompanied and interviewed. Six key values were identified contributing to job satisfaction - safeguarding these is crucial for successful robot implementation, including freedom and dislike of heavy work. Challenges were also identified, including labour shortages and reduced efficiency.
To determine where a robot could add value, three main waste problems in Amsterdam were identified and analysed. Inefficient waste management and littering behaviour were often the cause. To understand this behaviour, key influencing factors were identified and used in the analysis and thesis.
Furthermore, by analysing key factors of waste management behaviour, it was found that a cleaning robot can potentially trigger motivators for littering behaviour, suggesting that the robot's task influences waste management behaviour. Furthermore, when identifying factors influencing HRI, it was found that rewarding interactions can motivate proper behaviour, suggesting that robots can contribute to a cleaner environment without having to clean.
Based on the findings, specific requirements and a design vision for the robot were established, emphasising promoting proper waste management behaviour, ownership and waste management efficiency. To communicate the vision to the municipality, two concepts were developed, the Mobile Robot Bin and Mobile Robot Container. The Robot Bin aims to motivate proper behaviour through rewarding interactions and to increase waste collection efficiency. To align with Amsterdam's identity and raise awareness, the appearance will be created in collaboration with local artists.
The Robot Container focuses on providing waste disposal options at will in the city centre, optimising waste management efficiency and reducing littering behaviour, as the current policy allows residents to place waste outside twice a week. The concept reduces the physical burden on employees by eliminating the need to collect waste from the street and minimises the need for heavy waste trucks in the centre.
To assess the concepts’ value and feasibility in contributing to a cleaner Amsterdam, stakeholders from the municipality of Amsterdam, department Schoon and AMS Institute evaluated them. Both received positive feedback, with the Robot Container being identified as the most promising solution for achieving a cleaner Amsterdam. However, challenges such as vandalism need to be addressed before implementation. Nevertheless, stakeholders were enthusiastic and asked about implementation activities. A roadmap outlining these activities was developed and evaluated by the AMS expert. However, further research is needed to develop and implement the robots to achieve a cleaner Amsterdam.
To further analyse the context, employees of department Schoon were accompanied and interviewed. Six key values were identified contributing to job satisfaction - safeguarding these is crucial for successful robot implementation, including freedom and dislike of heavy work. Challenges were also identified, including labour shortages and reduced efficiency.
To determine where a robot could add value, three main waste problems in Amsterdam were identified and analysed. Inefficient waste management and littering behaviour were often the cause. To understand this behaviour, key influencing factors were identified and used in the analysis and thesis.
Furthermore, by analysing key factors of waste management behaviour, it was found that a cleaning robot can potentially trigger motivators for littering behaviour, suggesting that the robot's task influences waste management behaviour. Furthermore, when identifying factors influencing HRI, it was found that rewarding interactions can motivate proper behaviour, suggesting that robots can contribute to a cleaner environment without having to clean.
Based on the findings, specific requirements and a design vision for the robot were established, emphasising promoting proper waste management behaviour, ownership and waste management efficiency. To communicate the vision to the municipality, two concepts were developed, the Mobile Robot Bin and Mobile Robot Container. The Robot Bin aims to motivate proper behaviour through rewarding interactions and to increase waste collection efficiency. To align with Amsterdam's identity and raise awareness, the appearance will be created in collaboration with local artists.
The Robot Container focuses on providing waste disposal options at will in the city centre, optimising waste management efficiency and reducing littering behaviour, as the current policy allows residents to place waste outside twice a week. The concept reduces the physical burden on employees by eliminating the need to collect waste from the street and minimises the need for heavy waste trucks in the centre.
To assess the concepts’ value and feasibility in contributing to a cleaner Amsterdam, stakeholders from the municipality of Amsterdam, department Schoon and AMS Institute evaluated them. Both received positive feedback, with the Robot Container being identified as the most promising solution for achieving a cleaner Amsterdam. However, challenges such as vandalism need to be addressed before implementation. Nevertheless, stakeholders were enthusiastic and asked about implementation activities. A roadmap outlining these activities was developed and evaluated by the AMS expert. However, further research is needed to develop and implement the robots to achieve a cleaner Amsterdam.
TermiteSim
Developing a termite-like builder swarm simulator for experimantation and validation of control strategies
Automation in the form of swarm robots is an increasingly feasible opportunity for solving complex physical problems. However, how such a swarm is to be instructed and controlled is one of the many topics that requires further research. For this, we can look to nature for inspiration, as there are many nest building swarms. Perhaps the most notable of which are the mound building termites. These termites build incredibly intricate mounds that contain a royal chamber, nurseries, fungal gardens, covered walkways, and even ventilation shafts to thermoregulate the inside of the mound. There are some attempts to capture this behaviour in custom simulators. The problem is that these simulators have limited capabilities. That is why a new simulator specifically for termite-like builder robot swarms is required for further research in this field. In this project, the different requirements for such a simulator are identified and used to develop an open-source state of the art simulator, TermiteSim. TermiteSim is designed for experimenting with different control strategies and tuning the simulation parameters to recreate the desired behaviour. In other words: a tool for researchers to design desired behaviour of a builder robot swarm. In this thesis TermiteSim is used to simulate several termite-like building behaviours described in the literature and the resulting structures are compared to those of other simulators, which TermiteSim was successfully able to recreate.
...
Automation in the form of swarm robots is an increasingly feasible opportunity for solving complex physical problems. However, how such a swarm is to be instructed and controlled is one of the many topics that requires further research. For this, we can look to nature for inspiration, as there are many nest building swarms. Perhaps the most notable of which are the mound building termites. These termites build incredibly intricate mounds that contain a royal chamber, nurseries, fungal gardens, covered walkways, and even ventilation shafts to thermoregulate the inside of the mound. There are some attempts to capture this behaviour in custom simulators. The problem is that these simulators have limited capabilities. That is why a new simulator specifically for termite-like builder robot swarms is required for further research in this field. In this project, the different requirements for such a simulator are identified and used to develop an open-source state of the art simulator, TermiteSim. TermiteSim is designed for experimenting with different control strategies and tuning the simulation parameters to recreate the desired behaviour. In other words: a tool for researchers to design desired behaviour of a builder robot swarm. In this thesis TermiteSim is used to simulate several termite-like building behaviours described in the literature and the resulting structures are compared to those of other simulators, which TermiteSim was successfully able to recreate.
Fitness 2.0
Enabling a safe experience in a VR-based robotic platform
Providing a bodily injury-free experience might be a promising opportunity for the adoption of VR and force feedback-based equipment in a gym context. Nevertheless, it is still uncertain how these systems could compromise the users’ physical state and how they should react a posteriori.
This Graduation project begins with the exploration of the bodily injury risks associated with the Ethereal Engine, an ultimate VR-based equipment that seeks a revolution in the fitness industry. Resulting in four different clusters -collision, posture, balance loss and long-term exposure-related risks-, a study on the current market-ready technologies that could minimize these risks is performed together with an assessment on how safety can be boosted while keeping the experience’s engagement.
Thanks to the research, posture evaluation is selected as the challenge with a differential potential over the rest to bring Ethereal Engine to the next level, providing an experience in which bodily injury risks could be reduced, motivating users to adopt better postural habits when working out. Right after, a design vision is formulated, emphasizing the need for inspiring users to self-correct their posture instead of imposing rules in order to avoid possible immersion breakages.
In this context, three concepts are proposed, which present different feedback alternatives that vary in terms of explicitness, immediacy, and strictness. However, a priori there is no clear answer on which of these alternatives could most positively affect the experience. To overcome the knowledge gap an experiment that not only assesses the performance of the 16 participants but also their perception of the understandability, usefulness, performance, posture correction, general engagement, confusion and criticism of the feedback is conducted. During three different experiments where different feedback alternatives are assessed -immediate visual clues, statistics after certain repetitions, and immediate pop-up messages- participants are asked to perform 10 squats while lifting a water jug and receiving different scores depending on its displacement.
In order to do so, a partial prototype that allows for the first time to experience certain functionalities of the Ethereal Engine is developed. These functions are: a) a hybrid MoCap system that merges a Oculus Quest headset with a multi-camera-based skeletal tracking system -named MoCapForAll-. ; b) a calibration process that adjusts the range of motion according to the participant’s height; and, c) a demo game that enables a more intense workout while keeping track of your posture while squatting.
After discussing the results, including a calibration process that enables fair competitiveness and feedback at three different levels to communicate diverse information are spotted as desired features to include in the Ethereal Engine. Through these recommendations a virtual trainer that inspires users to self-correct their posture will be possible, and, subsequently, enabling a bodily injury-free experience. ...
This Graduation project begins with the exploration of the bodily injury risks associated with the Ethereal Engine, an ultimate VR-based equipment that seeks a revolution in the fitness industry. Resulting in four different clusters -collision, posture, balance loss and long-term exposure-related risks-, a study on the current market-ready technologies that could minimize these risks is performed together with an assessment on how safety can be boosted while keeping the experience’s engagement.
Thanks to the research, posture evaluation is selected as the challenge with a differential potential over the rest to bring Ethereal Engine to the next level, providing an experience in which bodily injury risks could be reduced, motivating users to adopt better postural habits when working out. Right after, a design vision is formulated, emphasizing the need for inspiring users to self-correct their posture instead of imposing rules in order to avoid possible immersion breakages.
In this context, three concepts are proposed, which present different feedback alternatives that vary in terms of explicitness, immediacy, and strictness. However, a priori there is no clear answer on which of these alternatives could most positively affect the experience. To overcome the knowledge gap an experiment that not only assesses the performance of the 16 participants but also their perception of the understandability, usefulness, performance, posture correction, general engagement, confusion and criticism of the feedback is conducted. During three different experiments where different feedback alternatives are assessed -immediate visual clues, statistics after certain repetitions, and immediate pop-up messages- participants are asked to perform 10 squats while lifting a water jug and receiving different scores depending on its displacement.
In order to do so, a partial prototype that allows for the first time to experience certain functionalities of the Ethereal Engine is developed. These functions are: a) a hybrid MoCap system that merges a Oculus Quest headset with a multi-camera-based skeletal tracking system -named MoCapForAll-. ; b) a calibration process that adjusts the range of motion according to the participant’s height; and, c) a demo game that enables a more intense workout while keeping track of your posture while squatting.
After discussing the results, including a calibration process that enables fair competitiveness and feedback at three different levels to communicate diverse information are spotted as desired features to include in the Ethereal Engine. Through these recommendations a virtual trainer that inspires users to self-correct their posture will be possible, and, subsequently, enabling a bodily injury-free experience. ...
Providing a bodily injury-free experience might be a promising opportunity for the adoption of VR and force feedback-based equipment in a gym context. Nevertheless, it is still uncertain how these systems could compromise the users’ physical state and how they should react a posteriori.
This Graduation project begins with the exploration of the bodily injury risks associated with the Ethereal Engine, an ultimate VR-based equipment that seeks a revolution in the fitness industry. Resulting in four different clusters -collision, posture, balance loss and long-term exposure-related risks-, a study on the current market-ready technologies that could minimize these risks is performed together with an assessment on how safety can be boosted while keeping the experience’s engagement.
Thanks to the research, posture evaluation is selected as the challenge with a differential potential over the rest to bring Ethereal Engine to the next level, providing an experience in which bodily injury risks could be reduced, motivating users to adopt better postural habits when working out. Right after, a design vision is formulated, emphasizing the need for inspiring users to self-correct their posture instead of imposing rules in order to avoid possible immersion breakages.
In this context, three concepts are proposed, which present different feedback alternatives that vary in terms of explicitness, immediacy, and strictness. However, a priori there is no clear answer on which of these alternatives could most positively affect the experience. To overcome the knowledge gap an experiment that not only assesses the performance of the 16 participants but also their perception of the understandability, usefulness, performance, posture correction, general engagement, confusion and criticism of the feedback is conducted. During three different experiments where different feedback alternatives are assessed -immediate visual clues, statistics after certain repetitions, and immediate pop-up messages- participants are asked to perform 10 squats while lifting a water jug and receiving different scores depending on its displacement.
In order to do so, a partial prototype that allows for the first time to experience certain functionalities of the Ethereal Engine is developed. These functions are: a) a hybrid MoCap system that merges a Oculus Quest headset with a multi-camera-based skeletal tracking system -named MoCapForAll-. ; b) a calibration process that adjusts the range of motion according to the participant’s height; and, c) a demo game that enables a more intense workout while keeping track of your posture while squatting.
After discussing the results, including a calibration process that enables fair competitiveness and feedback at three different levels to communicate diverse information are spotted as desired features to include in the Ethereal Engine. Through these recommendations a virtual trainer that inspires users to self-correct their posture will be possible, and, subsequently, enabling a bodily injury-free experience.
This Graduation project begins with the exploration of the bodily injury risks associated with the Ethereal Engine, an ultimate VR-based equipment that seeks a revolution in the fitness industry. Resulting in four different clusters -collision, posture, balance loss and long-term exposure-related risks-, a study on the current market-ready technologies that could minimize these risks is performed together with an assessment on how safety can be boosted while keeping the experience’s engagement.
Thanks to the research, posture evaluation is selected as the challenge with a differential potential over the rest to bring Ethereal Engine to the next level, providing an experience in which bodily injury risks could be reduced, motivating users to adopt better postural habits when working out. Right after, a design vision is formulated, emphasizing the need for inspiring users to self-correct their posture instead of imposing rules in order to avoid possible immersion breakages.
In this context, three concepts are proposed, which present different feedback alternatives that vary in terms of explicitness, immediacy, and strictness. However, a priori there is no clear answer on which of these alternatives could most positively affect the experience. To overcome the knowledge gap an experiment that not only assesses the performance of the 16 participants but also their perception of the understandability, usefulness, performance, posture correction, general engagement, confusion and criticism of the feedback is conducted. During three different experiments where different feedback alternatives are assessed -immediate visual clues, statistics after certain repetitions, and immediate pop-up messages- participants are asked to perform 10 squats while lifting a water jug and receiving different scores depending on its displacement.
In order to do so, a partial prototype that allows for the first time to experience certain functionalities of the Ethereal Engine is developed. These functions are: a) a hybrid MoCap system that merges a Oculus Quest headset with a multi-camera-based skeletal tracking system -named MoCapForAll-. ; b) a calibration process that adjusts the range of motion according to the participant’s height; and, c) a demo game that enables a more intense workout while keeping track of your posture while squatting.
After discussing the results, including a calibration process that enables fair competitiveness and feedback at three different levels to communicate diverse information are spotted as desired features to include in the Ethereal Engine. Through these recommendations a virtual trainer that inspires users to self-correct their posture will be possible, and, subsequently, enabling a bodily injury-free experience.
A Cleaner Public Space Through Robots
An exploratory research into the introduction of a cleaning robot in the Amsterdam Schoon department
The Dutch metropolis of Amsterdam deals with a waste problem. Both the inhabitants and tourists in Amsterdam experience nuisance from litter. The future growth of Amsterdam will only amplify this problem. To address this, the municipality needs to increase the productivity of the Schoon department, the department tasked with keeping the public space of Amsterdam clean. Therefore, the responsible and effective introduction of a cleaning robot is researched. During a series of walk-along days, interviews, experiments and observations, I identified multiple themes, important for the job satisfaction of the Schoon employees. This knowledge, combined with observed knowledge on practical challenges caused by the design of the Amsterdam public space on the cleaning activities, translates into a number of design qualities for a future cleaning robot. The results of this research seem to indicate that this cleaning robot could best be deployed during the shifts tasked with brooming the streets and emptying the trash bins, the Veegshift and Vuilnisbakkenshift respectively. During those shifts it can potentially assist in cleaning the street using the RAVO mechanical streetsweeper and emptying trash bins respectively. Assisting during those two tasks frees up manpower that can be utilized to increase the productivity of those shifts. The findings further highlight that this future robot should not compromise the freedom experienced by the Schoon employees in how they carry out their work. Nor should this robot replace the Schoon employees, as this would remove the human interaction with bystanders, an aspect of the work greatly appreciated by the employees. The loss of human interaction might also lead to a more monotonous situation, which is the opposite of the variety enjoyed by the Schoon employees during their work. The future robot should also be user friendly, allowing everyone in the department to operate the robot. Furthermore, the robot must be able to communicate its status, intentions and possible help requests and offers to its Schoon colleagues. Overall, the introduction of a cleaning robot can improve the cleanliness of the city of Amsterdam when the design incorporates the themes important for the job satisfaction of the Schoon employees, aims at an efficient human-robot collaboration through clear communication and combines the right type of autonomy with the challenging Amsterdam environment.
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The Dutch metropolis of Amsterdam deals with a waste problem. Both the inhabitants and tourists in Amsterdam experience nuisance from litter. The future growth of Amsterdam will only amplify this problem. To address this, the municipality needs to increase the productivity of the Schoon department, the department tasked with keeping the public space of Amsterdam clean. Therefore, the responsible and effective introduction of a cleaning robot is researched. During a series of walk-along days, interviews, experiments and observations, I identified multiple themes, important for the job satisfaction of the Schoon employees. This knowledge, combined with observed knowledge on practical challenges caused by the design of the Amsterdam public space on the cleaning activities, translates into a number of design qualities for a future cleaning robot. The results of this research seem to indicate that this cleaning robot could best be deployed during the shifts tasked with brooming the streets and emptying the trash bins, the Veegshift and Vuilnisbakkenshift respectively. During those shifts it can potentially assist in cleaning the street using the RAVO mechanical streetsweeper and emptying trash bins respectively. Assisting during those two tasks frees up manpower that can be utilized to increase the productivity of those shifts. The findings further highlight that this future robot should not compromise the freedom experienced by the Schoon employees in how they carry out their work. Nor should this robot replace the Schoon employees, as this would remove the human interaction with bystanders, an aspect of the work greatly appreciated by the employees. The loss of human interaction might also lead to a more monotonous situation, which is the opposite of the variety enjoyed by the Schoon employees during their work. The future robot should also be user friendly, allowing everyone in the department to operate the robot. Furthermore, the robot must be able to communicate its status, intentions and possible help requests and offers to its Schoon colleagues. Overall, the introduction of a cleaning robot can improve the cleanliness of the city of Amsterdam when the design incorporates the themes important for the job satisfaction of the Schoon employees, aims at an efficient human-robot collaboration through clear communication and combines the right type of autonomy with the challenging Amsterdam environment.
Last-mile delivery robots intended to operate on the sidewalk still require supervision because they are only semi-autonomous. If left to their own devices, they tend to cause undesired interactions. Our project proposes a design philosophy that can reduce the amount and severity of these interactions, improving the overall acceptance of sidewalk delivery robots. Our proposed design philosophy uses the power of expressive movement to create delivery robots with a streetwise attitude. Being streetwise means possessing behavioural qualities that allow you to deal with the potential difficulties of an urban environment. Using creative association, we narrowed these qualities down to confidence, pride, calmness, stability and smoothness. A design probe study confirmed that the streetwise qualities can be used to differentiate between desirable and undesirable events. Next, we propose a methodology to combine our streetwise qualities with movement theories. We verify the efficacy of the method in a 2D movement study. The results suggest that our interpretation of the movement theories is on the right track, but more iterations are necessary to improve the method's reliability. During our final evaluation, we combine all our findings in a 3D video prototype scenario to confirm if they hold up in a more realistic and relatable context. We showed participants two different versions of this scenario to compare a streetwise delivery robot with a non-streetwise delivery robot in terms of desirability. Both versions turned out to have positives and negatives, but overall, the streetwise robot appeared more favourable.
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Last-mile delivery robots intended to operate on the sidewalk still require supervision because they are only semi-autonomous. If left to their own devices, they tend to cause undesired interactions. Our project proposes a design philosophy that can reduce the amount and severity of these interactions, improving the overall acceptance of sidewalk delivery robots. Our proposed design philosophy uses the power of expressive movement to create delivery robots with a streetwise attitude. Being streetwise means possessing behavioural qualities that allow you to deal with the potential difficulties of an urban environment. Using creative association, we narrowed these qualities down to confidence, pride, calmness, stability and smoothness. A design probe study confirmed that the streetwise qualities can be used to differentiate between desirable and undesirable events. Next, we propose a methodology to combine our streetwise qualities with movement theories. We verify the efficacy of the method in a 2D movement study. The results suggest that our interpretation of the movement theories is on the right track, but more iterations are necessary to improve the method's reliability. During our final evaluation, we combine all our findings in a 3D video prototype scenario to confirm if they hold up in a more realistic and relatable context. We showed participants two different versions of this scenario to compare a streetwise delivery robot with a non-streetwise delivery robot in terms of desirability. Both versions turned out to have positives and negatives, but overall, the streetwise robot appeared more favourable.
Doplor Sleep
Friendly feedback towards a better hospital soundscape for sleep
Recently in the Netherlands, researchers have found that sleep duration and quality were suboptimal in the hospital. Evidence proved that many modifiable hospitalrelated factors negatively associate with patients' sleep (JAMA Internal Medicine, 2018). The sound factor is the most significant sleep disturbance in the hospital. In this graduation project, collaborating with Reiner de Graaf hospital and Critical Alarms lab, an information exchange system was proposed to raise awareness of sound as sleep disturbance. The system captures the sound-producing events and visualizes them with visually attractive graphics. In this system, we use the smartphone as the sound captor. The recorded sounds are processed locally on the phone and converted into information such as sound level and the category it belongs to (alarm, speech, incidental sounds, or snore). Fitbit is implemented in the system to collect sleep information. To both patients and medical staff, The Doplor sleep system presents the influence of sound on sleep in a friendly and comprehensive way. During this project, a functioning prototype was developed. We have tested its functionality and user experience with the potential users.
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Recently in the Netherlands, researchers have found that sleep duration and quality were suboptimal in the hospital. Evidence proved that many modifiable hospitalrelated factors negatively associate with patients' sleep (JAMA Internal Medicine, 2018). The sound factor is the most significant sleep disturbance in the hospital. In this graduation project, collaborating with Reiner de Graaf hospital and Critical Alarms lab, an information exchange system was proposed to raise awareness of sound as sleep disturbance. The system captures the sound-producing events and visualizes them with visually attractive graphics. In this system, we use the smartphone as the sound captor. The recorded sounds are processed locally on the phone and converted into information such as sound level and the category it belongs to (alarm, speech, incidental sounds, or snore). Fitbit is implemented in the system to collect sleep information. To both patients and medical staff, The Doplor sleep system presents the influence of sound on sleep in a friendly and comprehensive way. During this project, a functioning prototype was developed. We have tested its functionality and user experience with the potential users.
Many people experience worry once in a while. Chronic worry can have a severe impact on people's daily life. Many things, like health conditions, social relationships, sleep quality, and work performance, are all influenced by worrying [Joseph 2017]. So, this is something we would like to address. This assignment aims to explore embodied interactions to help people reduce worries and improve their well-being.
To understand what people are worried about, how they start worrying, and what people do when worrying, I designed a culture probe, with wristband, stickers, and reports. The culture probe aims to capture the moment when the users are worrying. There were 16 participants in this research, providing 90 worry reports[Appendix-2].
From the analysis of culture probe, I narrowed the scope into the design goals: Monitor people's worry level, relieve people's negative feelings, remind people who are stuck in the negative feelings and distract people when they perceive low controllability.
After that, I did competitive research about mental health Apps and therapeutic robots on the market. This research is to analyze the interactions they provide, why they work/do not work. Combining with literature reviews, I came up with the interaction vision describing how the interaction should be. The most essential visions are Inviting, subtle& natural, socially autonomous, and meaningful.
Then, in the ideation phase, I did two brainstorming sessions to explore interactions to relieve people's negative feelings, how to detect their worrying feelings and how to make the interaction intuitively relate to the worries. There were also two evaluation sessions in the ideation phase, which helped me develop the ideas into three concepts.
In the conceptualization phase, I developed three concepts further and arranged a peer evaluation session to determine the final concept, the zen stone concept. Then I did a low-fi prototype test to find out it the idea fits the design goal & interaction vision. The result was very promising; the interaction helped the user to relieve their negative feelings. So I decided to develop the concept further with an App providing guidance. Then I arranged the final usability test and iterated the concept with some details.
The final design's name is Zen stone. It can recognize the user's emotions with emotion recognition by speech software and remind the user when they are worrying, though shining and vibrating. The zen stone will mimic the user's heart rate through a sensor, helping the user be aware of their mental state. It will also provide meditation guidance to help to user calm down and focus on the moment.
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Many people experience worry once in a while. Chronic worry can have a severe impact on people's daily life. Many things, like health conditions, social relationships, sleep quality, and work performance, are all influenced by worrying [Joseph 2017]. So, this is something we would like to address. This assignment aims to explore embodied interactions to help people reduce worries and improve their well-being.
To understand what people are worried about, how they start worrying, and what people do when worrying, I designed a culture probe, with wristband, stickers, and reports. The culture probe aims to capture the moment when the users are worrying. There were 16 participants in this research, providing 90 worry reports[Appendix-2].
From the analysis of culture probe, I narrowed the scope into the design goals: Monitor people's worry level, relieve people's negative feelings, remind people who are stuck in the negative feelings and distract people when they perceive low controllability.
After that, I did competitive research about mental health Apps and therapeutic robots on the market. This research is to analyze the interactions they provide, why they work/do not work. Combining with literature reviews, I came up with the interaction vision describing how the interaction should be. The most essential visions are Inviting, subtle& natural, socially autonomous, and meaningful.
Then, in the ideation phase, I did two brainstorming sessions to explore interactions to relieve people's negative feelings, how to detect their worrying feelings and how to make the interaction intuitively relate to the worries. There were also two evaluation sessions in the ideation phase, which helped me develop the ideas into three concepts.
In the conceptualization phase, I developed three concepts further and arranged a peer evaluation session to determine the final concept, the zen stone concept. Then I did a low-fi prototype test to find out it the idea fits the design goal & interaction vision. The result was very promising; the interaction helped the user to relieve their negative feelings. So I decided to develop the concept further with an App providing guidance. Then I arranged the final usability test and iterated the concept with some details.
The final design's name is Zen stone. It can recognize the user's emotions with emotion recognition by speech software and remind the user when they are worrying, though shining and vibrating. The zen stone will mimic the user's heart rate through a sensor, helping the user be aware of their mental state. It will also provide meditation guidance to help to user calm down and focus on the moment.