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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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Casao, S. (author), Serra Gomez, A. (author), Murillo, Ana C. (author), Böhmer, J.W. (author), Alonso-Mora, J. (author), Montijano, Eduardo (author)
Smart cameras are an essential component in surveillance and monitoring applications, and they have been typically deployed in networks of fixed camera locations. The addition of mobile cameras, mounted on robots, can overcome some of the limitations of static networks such as blind spots or back-lightning, allowing the system to gather the...
journal article 2024
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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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Bakker, S. (author), Knödler, L. (author), Spahn, M. (author), Böhmer, J.W. (author), Alonso-Mora, J. (author)
In this paper, we address the problem of real-time motion planning for multiple robotic manipulators that operate in close proximity. We build upon the concept of dynamic fabrics and extend them to multi-robot systems, referred to as Multi-Robot Dynamic Fabrics (MRDF). This geometric method enables a very high planning frequency for high...
conference paper 2024
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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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Wang, X. (author), Li, Zirui (author), Alonso-Mora, J. (author), Wang, Meng (author)
Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles. Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions. However, they suffer from over-conservatism, potentially resulting in false–positive risk events in...
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....
journal article 2024
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Ferranti, L. (author), Lyons, L. (author), Negenborn, R.R. (author), Keviczky, T. (author), Alonso-Mora, J. (author)
This work presents a method for multi-robot coordination based on a novel distributed nonlinear model predictive control (NMPC) formulation for trajectory optimization and its modified version to mitigate the effects of packet losses and delays in the communication among the robots. Our algorithms consider that each robot is equipped with an...
journal article 2023
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Spahn, M. (author), Wisse, M. (author), Alonso-Mora, J. (author)
Optimization fabrics are a geometric approach to real-time local motion generation, where motions are designed by the composition of several differential equations that exhibit a desired motion behavior. We generalize this framework to dynamic scenarios and nonholonomic robots and prove that fundamental properties can be conserved. We show...
journal article 2023
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Fielbaum, Andres (author), Tirachini, Alejandro (author), Alonso-Mora, J. (author)
We analyse the sources of economies and diseconomies of scale in On-Demand Ridepooling (ODRP), disentangling three effects: when demand grows, average costs are reduced due to i) a larger fleet that diminishes waiting and walking times (Mohring Effect), and ii) matching users with more similar routes (Better-matching Effect). A counter...
journal article 2023
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de Ruijter, A.J.F. (author), Cats, O. (author), Alonso-Mora, J. (author), Hoogendoorn, S.P. (author)
Previous studies into the potential benefits of ride pooling failed to account for the trade-off that users likely make when considering a shared ride. We address this shortcoming by formulating user net benefit stemming from pooling as a compensatory function where the additional travel time and on-board discomfort need to be compensated by...
journal article 2023
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Serra Gomez, A. (author), Montijano, Eduardo (author), Böhmer, J.W. (author), Alonso-Mora, J. (author)
In this paper, we consider the problem where a drone has to collect semantic information to classify multiple moving targets. In particular, we address the challenge of computing control inputs that move the drone to informative viewpoints, position and orientation, when the information is extracted using a “black-box” classifier, e.g., a deep...
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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Voogd, Kevin L. (author), Allamaa, Jean Pierre (author), Alonso-Mora, J. (author), Son, Tong Duy (author)
Reinforcement learning (RL) is a promising solution for autonomous vehicles to deal with complex and uncertain traffic environments. The RL training process is however expensive, unsafe, and time-consuming. Algorithms are often developed first in simulation and then transferred to the real-world, leading to a common sim2real challenge where...
journal article 2023
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Li, Jingqi (author), Chiu, Chih Yuan (author), Peters, L. (author), Palafox, Fernando (author), Karabag, Mustafa (author), Alonso-Mora, J. (author), Sojoudi, Somayeh (author), Tomlin, Claire (author), Fridovich-Keil, David (author)
Decision-making in multi-player games can be extremely challenging, particularly under uncertainty. In this work, we propose a new sample-based approximation to a class of stochastic, general-sum, pure Nash games, where each player has an expected-value objective and a set of chance constraints. This new approximation scheme inherits the...
conference paper 2023
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Khaled Mustafa, K.A. (author), de Groot, O.M. (author), Wang, X. (author), Kober, J. (author), Alonso-Mora, J. (author)
Balancing safety and efficiency when planning in crowded scenarios with uncertain dynamics is challenging where it is imperative to accomplish the robot's mission without incurring any safety violations. Typically, chance constraints are incorporated into the planning problem to provide probabilistic safety guarantees by imposing an upper bound...
conference paper 2023
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Wang, Weiying (author), Kemmeren, A.C. (author), Son, Daniel (author), Alonso-Mora, J. (author), Gil, Stephanie (author)
In this paper we propose a novel algorithm, Wi-Closure, to improve the computational efficiency and robustness of loop closure detection in multi-robot SLAM. Our approach decreases the computational overhead of classical approaches by pruning the search space of potential loop closures, prior to evaluation by a typical multi-robot SLAM pipeline....
conference paper 2023
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Streichenberg, L.M. (author), Trevisan, E. (author), Chung, Jen Jen (author), Siegwart, R. (author), Alonso-Mora, J. (author)
Autonomous vehicles that operate in urban environments shall comply with existing rules and reason about the interactions with other decision-making agents. In this paper, we introduce a decentralized and communication-free interaction-aware motion planner and apply it to Autonomous Surface Vessels (ASVs) in urban canals. We build upon a...
conference paper 2023
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de Groot, O.M. (author), Ferranti, L. (author), Gavrila, D. (author), Alonso-Mora, J. (author)
Navigating mobile robots through environments shared with humans is challenging. From the perspective of the robot, humans are dynamic obstacles that must be avoided. These obstacles make the collision-free space nonconvex, which leads to two distinct passing behaviors per obstacle (passing left or right). For local planners, such as receding...
conference paper 2023
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Casao, S. (author), Otero, Andrés (author), Serra Gomez, A. (author), Murillo, Ana C. (author), Alonso-Mora, J. (author), Montijano, Eduardo (author)
Robotic applications involving people often require advanced perception systems to better understand complex real-world scenarios. To address this challenge, photo-realistic and physics simulators are gaining popularity as a means of generating accurate data labeling and designing scenarios for evaluating generalization capabilities, e.g.,...
conference paper 2023
Searched for: %2520
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