Searched for: author%3A%22Alonso+Mora%2C+J.%22
(1 - 20 of 84)

Pages

document
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
document
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
document
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
document
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
document
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
document
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
document
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
document
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
document
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
document
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
document
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
document
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
document
Peters, L. (author), Rubies-Royo, Vicenç (author), Tomlin, Claire J. (author), Ferranti, L. (author), Alonso Mora, J. (author), Stachniss, Cyrill (author), Fridovich-Keil, David (author)
Robots deployed to the real world must be able to interact with other agents in their environment. Dynamic game theory provides a powerful mathematical framework for modeling scenarios in which agents have individual objectives and interactions evolve over time. However, a key limitation of such techniques is that they require a priori...
journal article 2023
document
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
document
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
document
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
document
Wilde, N. (author), Alonso Mora, J. (author)
Reward learning is a highly active area of research in human-robot interaction (HRI), allowing a broad range of users to specify complex robot behaviour. Experiments with simulated user input play a major role in the development and evaluation of reward learning algorithms due to the availability of a ground truth. In this paper, we review...
journal article 2023
document
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
document
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
document
Spahn, M. (author), Alonso-Mora, J. (author)
In this paper, we present an automated parameter optimization method for trajectory generation. We formulate parameter optimization as a constrained optimization problem that can be effectively solved using Bayesian optimization. While the approach is generic to any trajectory generation method, we showcase it using optimization fabrics....
conference paper 2023
Searched for: author%3A%22Alonso+Mora%2C+J.%22
(1 - 20 of 84)

Pages