Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Lusk, Parker C."'
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
Autor:
Lusk, Parker C.
Data association is a fundamental requirement of geometric estimation in robotics. Identifying correspondences between measurements and models enables estimation processes to incorporate more data, in general leading to better estimates. However, sen
Externí odkaz:
https://hdl.handle.net/1721.1/152732
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 MOTLEE, a distributed mobile multi-object tracking algorithm that enables a team of robots to collaboratively track moving objects in the presence of localization error. Existing approaches to distributed tracking make limiting assumptions
Externí odkaz:
http://arxiv.org/abs/2304.12175
Autor:
Kondo, Kota, Figueroa, Reinaldo, Rached, Juan, Tordesillas, Jesus, Lusk, Parker C., How, Jonathan P.
Communication delays can be catastrophic for multiagent systems. However, most existing state-of-the-art multiagent trajectory planners assume perfect communication and therefore lack a strategy to rectify this issue in real-world environments. To ad
Externí odkaz:
http://arxiv.org/abs/2303.06222
We present a novel framework for global localization and guided relocalization of a vehicle in an unstructured environment. Compared to existing methods, our pipeline does not rely on cues from urban fixtures (e.g., lane markings, buildings), nor doe
Externí odkaz:
http://arxiv.org/abs/2303.04658
Publikováno v:
IEEE Robotics and Automation Letters, vol. 8, no. 2, pp. 632-639, Feb. 2023
Using geometric landmarks like lines and planes can increase navigation accuracy and decrease map storage requirements compared to commonly-used LiDAR point cloud maps. However, landmark-based registration for applications like loop closure detection
Externí odkaz:
http://arxiv.org/abs/2212.12745
Publikováno v:
IEEE Robotics and Automation Letters, vol. 8, no. 5, pp. 2462-2469, May 2023
We present a multiway fusion algorithm capable of directly processing uncertain pairwise affinities. In contrast to existing works that require initial pairwise associations, our MIXER algorithm improves accuracy by leveraging the additional informat
Externí odkaz:
http://arxiv.org/abs/2210.08360
Autor:
Kondo, Kota, Tordesillas, Jesus, Figueroa, Reinaldo, Rached, Juan, Merkel, Joseph, Lusk, Parker C., How, Jonathan P.
Although communication delays can disrupt multiagent systems, most of the existing multiagent trajectory planners lack a strategy to address this issue. State-of-the-art approaches typically assume perfect communication environments, which is hardly
Externí odkaz:
http://arxiv.org/abs/2209.13667