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Scalarizing Multi-Objective Robot Planning Problems Using Weighted Maximization

Wilde, N. (author), Smith, Stephen L. (author), Alonso-Mora, J. (author)

When designing a motion planner for autonomous robots there are usually multiple objectives to be considered. However, a cost function that yields the desired trade-off between objectives is not easily obtainable. A common technique across many applications is to use a weighted sum of relevant objective functions and then carefully adapt the...

journal article 2024

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Contingency Games for Multi-Agent Interaction

Peters, L. (author), Bajcsy, Andrea (author), Chiu, Chih Yuan (author), Fridovich-Keil, David (author), Laine, Forrest (author), Ferranti, L. (author), Alonso-Mora, J. (author)

Contingency planning, wherein an agent generates a set of possible plans conditioned on the outcome of an uncertain event, is an increasingly popular way for robots to act under uncertainty. In this work we take a game-theoretic perspective on contingency planning, tailored to multi-agent scenarios in which a robot's actions impact the...

journal article 2024

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Statistically Distinct Plans for Multi-Objective Task Assignment

Wilde, N. (author), Alonso-Mora, J. (author)

We study the problem of finding statistically distinct plans for stochastic task assignment problems such as online multi-robot pickup and delivery (MRPD) when facing multiple competing objectives. In many real-world settings robot fleets do not only need to fulfil delivery requests, but also have to consider auxiliary objectives such as...

journal article 2024

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A Q-learning based multi-strategy integrated artificial bee colony algorithm with application in unmanned vehicle path planning

Ni, Xinrui (author), Hu, Wei (author), Fan, Q. (author), Cui, Yibing (author), Qi, Chongkai (author)

Artificial bee colony (ABC) is a prominent algorithm that offers great exploration capabilities among various meta-heuristic algorithms. However, its monotonous and one-dimensional search strategy limits its searching performance in the solving process. Thus, to address this issue, a Q-learning based multi-strategy integrated ABC algorithm ...

journal article 2024

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Deformation Prediction and Autonomous Path Planning for Robot-Assisted Endovascular Interventions

Li, Z. (author)

Endovascular interventions, as emerging medical therapies, utilize blood vessels as conduits to access anatomically challenging regions deep within the body. Within endovascular interventions, one of the prominent challenges involves maneuvering the instrument tip by coordinating insertion, retraction, and torque actions at the proximal end of...

doctoral thesis 2023

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Free Energy Principle Based Precision Modulation for Robot Attention: Towards brain inspired robot intelligence

Anil Meera, A. (author)

The potential impact of a grand unified theory of the brain on the robotics community might be immense, as it might hold the key to the general artificial intelligence. Such a theory might make revolutionary leaps in robot intelligence by improving the quality of our lives. The last two decades have witnessed the rise of one such brain theory -...

doctoral thesis 2023

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Model Predictive Path Planning of AGVs: Mixed Logical Dynamical Formulation and Distributed Coordination

Xin, Jianbin (author), Wu, Xuwen (author), D'Ariano, Andrea (author), Negenborn, R.R. (author), Zhang, Fangfang (author)

Most of the existing path planning methods of automated guided vehicles (AGVs) are static. This paper proposes a new methodology for the path planning of a fleet of AGVs to improve the flexibility, robustness, and scalability of the AGV system. We mathematically describe the transport process as a dynamical system using an ad hoc mixed...

journal article 2023

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A risk-based driver behaviour model

Yuan, Y. (author), Wang, X. (author), Calvert, S.C. (author), Happee, R. (author), Wang, M. (author)

Current driver behaviour models (DBMs) are primarily designed for the general driver population under specific scenarios, such as car following or lane changing. Hence DBMs capturing individual behaviour under various scenarios are lacking. This paper presents a novel method to quantify individual perceived driving risk in the longitudinal...

journal article 2023

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A self-guided approach for navigation in a minimalistic foraging robotic swarm

Adams, S.J.L. (author), Jarne Ornia, D. (author), Mazo, M. (author)

We present a biologically inspired design for swarm foraging based on ant’s pheromone deployment, where the swarm is assumed to have very restricted capabilities. The robots do not require global or relative position measurements and the swarm is fully decentralized and needs no infrastructure in place. Additionally, the system only requires...

journal article 2023

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Multi-agent planning and coordination for automated aircraft ground handling

Chen, Szu Tung (author), Ermis, G. (author), Sharpanskykh, Alexei (author)

Inspired by the vision of fully autonomous airside operations at Schiphol airport, this study aims to contribute to the short-term goal of automated aircraft ground handling. In this research, we design and evaluate a multi-agent system for planning of automated ground handling. There are two main components in the system: task allocation...

journal article 2023

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Optimizing Task Waiting Times in Dynamic Vehicle Routing

Botros, Alexander (author), Gilhuly, Barry (author), Wilde, N. (author), Sadeghi, Armin (author), Alonso-Mora, J. (author), Smith, Stephen L. (author)

We study the problem of deploying a fleet of mobile robots to service tasks that arrive stochastically over time and at random locations in an environment. This is known as the Dynamic Vehicle Routing Problem (DVRP) and requires robots to allocate incoming tasks among themselves and find an optimal sequence for each robot. State-of-the-art...

journal article 2023

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An insertability constraint for shape optimization

Garner, E. (author), Wu, J. (author), Zadpoor, A.A. (author)

Patient-specific implants offer a host of benefits over their generic counterparts. Nonetheless, the design and optimization of these components present several technical challenges, among them being the need to ensure their insertability into the host bone tissue. This presents a significant challenge due to the tight-fitting nature of the...

journal article 2023

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RAST: Risk-Aware Spatio-Temporal Safety Corridors for MAV Navigation in Dynamic Uncertain Environments

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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Learning from Demonstrations of Critical Driving Behaviours Using Driver's Risk Field

Du, Yurui (author), Acerbo, Flavia Sofia (author), Kober, J. (author), Son, Tong Duy (author)

In recent years, imitation learning (IL) has been widely used in industry as the core of autonomous vehicle (AV) planning modules. However, previous IL works show sample inefficiency and low generalisation in safety-critical scenarios, on which they are rarely tested. As a result, IL planners can reach a performance plateau where adding more...

journal article 2023

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A route network planning method for urban air delivery

He, Xinyu (author), He, Fang (author), Li, L. (author), Zhang, Lei (author), Xiao, Gang (author)

High-tech giants and start-ups are investing in drone technologies to provide urban air delivery service, which is expected to solve the last-mile problem and mitigate road traffic congestion. However, air delivery service will not scale up without proper traffic management for drones in dense urban environment. Currently, a range of Concepts...

journal article 2022

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Distributed Model Predictive Contouring Control for Real-Time Multi-Robot Motion Planning

Xin, Jianbin (author), Qu, Yaoguang (author), Zhang, Fangfang (author), Negenborn, R.R. (author)

Existing motion planning algorithms for multi-robot systems must be improved to address poor coordination and increase low real-time performance. This paper proposes a new distributed real-time motion planning method for a multi-robot system using Model Predictive Contouring Control (MPCC). MPCC allows separating the tracking accuracy and...

journal article 2022

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Informative Path Planning in Random Fields via Mixed Integer Programming

Dutta, Shamak (author), Wilde, N. (author), Smith, Stephen L. (author)

We present a new mixed integer formulation for the discrete informative path planning problem in random fields. The objective is to compute a budget constrained path while collecting measurements whose linear estimate results in minimum error over a finite set of prediction locations. The problem is known to be NP-hard. However, we strive to...

conference paper 2022

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3D Path Planning for UAVs in Dynamic Environments in the Presence of Uncertainties

Zammit, C. (author)

Unmanned Aerial Vehicles (UAVs) are being integrated into all spheres of life, for a wide range of application in civil, commercial and military applications in both indoor and outdoor environments. UAV onboard intelligence is a paramount requirement in the realisation of UAV Traffic Management System (UTM) and Air Traffic Management (ATM)...

doctoral thesis 2021

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IOC based trajectory generation to increase human acceptance of robot motions in collaborative tasks

Hoogerwerf, Eert (author), Bharatheesha, M. (author), Clever, Debora (author)

Collaboration between humans and robots is an important aspect of Industry 4.0. It can be improved by incorporating human-like characteristics into robot motion planning. It is assumed that humans move optimal with respect to a certain objective or cost function. To find this function, also for a robot, we use an inverse optimal control...

journal article 2021

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Path planning for endovascular catheterization under curvature constraints via two-phase searching approach

Li, Z. (author), Dankelman, J. (author), De Momi, Elena (author)

Purpose: Planning a safe path for flexible catheters is one of the major challenges of endovascular catheterization. State-of-the-art methods rarely consider the catheter curvature constraint and reduced computational time of path planning which guarantees the possibility to re-plan the path during the actual operation. Methods: In this...

journal article 2021