Zobrazeno 1 - 10
of 787
pro vyhledávání: '"How, Jonathan P."'
Autor:
Kondo, Kota, Tewari, Claudius T., Tagliabue, Andrea, Tordesillas, Jesus, Lusk, Parker C., How, Jonathan P.
In decentralized multiagent trajectory planners, agents need to communicate and exchange their positions to generate collision-free trajectories. However, due to localization errors/uncertainties, trajectory deconfliction can fail even if trajectorie
Externí odkaz:
http://arxiv.org/abs/2406.10060
Knowing the locations of nearby moving objects is important for a mobile robot to operate safely in a dynamic environment. Dynamic object tracking performance can be improved if robots share observations of tracked objects with nearby team members in
Externí odkaz:
http://arxiv.org/abs/2405.05210
Despite notable successes of Reinforcement Learning (RL), the prevalent use of an online learning paradigm prevents its widespread adoption, especially in hazardous or costly scenarios. Offline RL has emerged as an alternative solution, learning from
Externí odkaz:
http://arxiv.org/abs/2405.03892
Autor:
Kondo, Kota, Tagliabue, Andrea, Cai, Xiaoyi, Tewari, Claudius, Garcia, Olivia, Espitia-Alvarez, Marcos, How, Jonathan P.
Traditional optimization-based planners, while effective, suffer from high computational costs, resulting in slow trajectory generation. A successful strategy to reduce computation time involves using Imitation Learning (IL) to develop fast neural ne
Externí odkaz:
http://arxiv.org/abs/2405.01758
Autor:
Aggarwal, Naman, How, Jonathan P.
The paper presents Maximal Covariance Backward Reachable Trees (MAXCOVAR BRT), which is a multi-query algorithm for planning of dynamic systems under stochastic motion uncertainty and constraints on the control input with explicit coverage guarantees
Externí odkaz:
http://arxiv.org/abs/2403.14605
Autor:
Sharma, Lakshay, How, Jonathan P.
To operate safely and efficiently, autonomous warehouse/delivery robots must be able to accomplish tasks while navigating in dynamic environments and handling the large uncertainties associated with the motions/behaviors of other robots and/or humans
Externí odkaz:
http://arxiv.org/abs/2403.13284
Autor:
Lusk, Parker C., How, Jonathan P.
Identifying correspondences in noisy data is a critically important step in estimation processes. When an informative initial estimation guess is available, the data association challenge is less acute; however, the existence of a high-quality initia
Externí odkaz:
http://arxiv.org/abs/2402.07284
We present SOS-Match, a novel framework for detecting and matching objects in unstructured environments. Our system consists of 1) a front-end mapping pipeline using a zero-shot segmentation model to extract object masks from images and track them ac
Externí odkaz:
http://arxiv.org/abs/2401.04791
Inter-agent relative localization is critical for many multi-robot systems operating in the absence of external positioning infrastructure or prior environmental knowledge. We propose a novel inter-agent relative 3D pose estimation system where each
Externí odkaz:
http://arxiv.org/abs/2312.17731
Autor:
Tagliabue, Andrea, How, Jonathan P.
Imitation learning (IL) can train computationally-efficient sensorimotor policies from a resource-intensive Model Predictive Controller (MPC), but it often requires many samples, leading to long training times or limited robustness. To address these
Externí odkaz:
http://arxiv.org/abs/2311.14153