Searched for: subject%3A%22collision%255C+avoidance%22
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Presa Magriña, Guillermo (author)
Throughout history, human progress has been defined by the mastery of materials, transitioning from stone and bronze to the steel age. However, this progression has not only been defined by the materials utilized but has also encompassed a shift in processes, moving from the industrial to the information era. Despite the advances in fabrication...
master thesis 2024
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Trip, Kenrick (author)
With the introduction of autonomous vehicles on public roads, their performance in emergency situations has become a strong focus. Collision Imminent Control (CIC) concerns the planning and control of aggressive evasive maneuvers for collision avoidance of automated vehicles. CIC is implemented using adaptive Nonlinear Model Predictive Control ...
master thesis 2024
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Bai, Chengchao (author), Yan, Peng (author), Piao, Haiyin (author), Pan, W. (author), Guo, Jifeng (author)
This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...
journal article 2024
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Trevisan, E. (author), Alonso-Mora, J. (author)
Motion planning for autonomous robots in dynamic environments poses numerous challenges due to uncertainties in the robot's dynamics and interaction with other agents. Sampling-based MPC approaches, such as Model Predictive Path Integral (MPPI) control, have shown promise in addressing these complex motion planning problems. However, the...
journal article 2024
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de Vries, Rinto (author)
Recent literature in real-time trajectory planning has proposed using Control Barrier Functions (CBFs) as collision constraints in Model Predictive Control (MPC) for efficient guidance, a concept referred to as MPC-CBF. This concept has been explored for both first and second-order CBFs. However, these approaches relied on an analytical...
master thesis 2023
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SHI, MOJI (author)
Dynamic obstacle avoidance remains a crucial research area for autonomous systems, such as Micro Aerial Vehicles (MAVs) and service robots. <br/>Efforts to develop dynamic collision avoidance techniques in unknown environments have proliferated in recent years. While these methods exhibit impressive and reliable performance in simpler...
master thesis 2023
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Wu, Siyuan (author)
Recent progress in multiple micro aerial vehicle (MAV) systems has demonstrated autonomous navigation in static environments. Yet, there are limited works regarding the autonomous navigation of multiple MAVs in dynamic and unknown environments. The challenge arises from the complexity of the motion planning problem, which requires the MAVs to...
master thesis 2023
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Capus, Luana (author)
Space debris has become a rising problem in the aerospace community, leading to the need for effective spacecraft collision avoidance processes. Currently, these processes can be called unilateral as only one object in conjunction is considered maneuverable. This thesis focuses on the implementation of a combined action approach to collision...
master thesis 2023
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van der Drift, Victor (author)
This thesis presents a comprehensive approach to integrating a trajectory planner and follower for autonomous vehicles (AVs) using model predictive contouring control (MPCC). The planner generates collision-free trajectories with a kinematic bicycle model, while the follower tracks them using a dynamic bicycle model with a smaller integration...
master thesis 2023
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LIU, Xinjie (author)
Many autonomous navigation tasks require mobile robots to operate in dynamic environments involving interactions between agents. Developing interaction-aware motion planning algorithms that enable safe and intelligent interactions remains challenging. Dynamic game theory renders a powerful mathematical framework to model these interactions...
master thesis 2023
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van Loon, Joaquin (author)
Situational awareness within port areas is crucial to avoid collisions, navigate efficiently and reduce congestion. Maritime-traffic controllers constantly monitor the situation in the port and intervene when needed. This study proposes a deep learning model that predicts future vessel positions to assist in this process. The model employs a...
master thesis 2023
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van Venrooij, Caspar (author)
Autonomous robots hold great potential for positive impacts on society by applying them to tasks that are hazardous, repetitive, or complex and difficult for humans to perform. To achieve these tasks, autonomous robots require the ability to perceive environmental changes and create corresponding motion plans, which involve a combination of...
master thesis 2023
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Rol, Remy (author)
master thesis 2023
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Liu, Kezhong (author), Wu, Xiaolie (author), Zhou, Y. (author), Yuan, Zhitao (author), Yang, Xing (author), Xin, Xuri (author), Zhuang, Sujie (author)
During the process of collision avoidance, especially in a multi-ship encounter situation, the dynamic interactions among individual ships impose a significant impact on collision avoidance decision-making. It is imperative, therefore, that collision avoidance decisions are formulated with a comprehensive consideration of not only the current...
journal article 2023
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Chen, Gang (author), Dong, Wei (author), Peng, Peng (author), Alonso-Mora, J. (author), Zhu, Xiangyang (author)
Particle-based dynamic occupancy maps were proposed in recent years to model the obstacles in dynamic environments. Current particle-based maps describe the occupancy status in discrete grid form and suffer from the grid size problem, wherein a large grid size is unfavorable for motion planning while a small grid size lowers efficiency and...
journal article 2023
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Liu, Xinjie (author), Peters, L. (author), Alonso-Mora, J. (author)
Many autonomous agents, such as intelligent vehicles, are inherently required to interact with one another. Game theory provides a natural mathematical tool for robot motion planning in such interactive settings. However, tractable algorithms for such problems usually rely on a strong assumption, namely that the objectives of all players in...
journal article 2023
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Angelini, Franco (author), Angelini, Pierangela (author), Angiolini, Claudia (author), Bagella, Simonetta (author), Caccianiga, Marco (author), Della Santina, C. (author), Gigante, Daniela (author), Hutter, Marco (author), Nanayakkara, Thrishantha (author)
In this paper, we first discuss the challenges related to habitat monitoring and review possible robotic solutions. Then, we propose a framework to perform terrestrial habitat monitoring exploiting the mobility of legged robotic systems. The idea is to provide the robot with the Natural Intelligence introduced as the combination of the...
journal article 2023
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Serra Gomez, A. (author), Zhu, H. (author), Ferreira de Brito, B.F. (author), Böhmer, J.W. (author), Alonso-Mora, J. (author)
Decentralized multi-robot systems typically perform coordinated motion planning by constantly broadcasting their intentions to avoid collisions. However, the risk of collision between robots varies as they move and communication may not always be needed. This paper presents an efficient communication method that addresses the problem of “when...
journal article 2023
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Bai, X. (author), Fielbaum, Andres (author), Kronmüller, M. (author), Knödler, L. (author), Alonso-Mora, J. (author)
This paper studies the multi-robot task assignment problem in which a fleet of dispersed robots needs to efficiently transport a set of dynamically appearing packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity. Given a...
journal article 2023
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Cheng, Gang (author), Wu, S. (author), Shi, M. (author), Dong, W. (author), Zhu, H. (author), Alonso-Mora, J. (author)
Autonomous navigation of Micro Aerial Vehicles (MAVs) in dynamic and unknown environments is a complex and challenging task. Current works rely on assumptions to solve the problem. The MAV's pose is precisely known, the dynamic obstacles can be explicitly segmented from static ones, their number is known and fixed, or they can be modeled with...
journal article 2023
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