Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Kumar, T. K. Satish"'
Multi-Agent Path Finding (MAPF), which involves finding collision-free paths for multiple robots, is crucial in various applications. Lifelong MAPF, where targets are reassigned to agents as soon as they complete their initial targets, offers a more
Externí odkaz:
http://arxiv.org/abs/2403.13421
Neural Networks and related Deep Learning methods are currently at the leading edge of technologies used for classifying objects. However, they generally demand large amounts of time and data for model training; and their learned models can sometimes
Externí odkaz:
http://arxiv.org/abs/2204.05112
Publikováno v:
Proceedings of the Twelfth International Symposium on Combinatorial Search (2020), 48-57
Embedding undirected graphs in a Euclidean space has many computational benefits. FastMap is an efficient embedding algorithm that facilitates a geometric interpretation of problems posed on undirected graphs. However, Euclidean distances are inheren
Externí odkaz:
http://arxiv.org/abs/2006.03112
Autor:
Li, Jiaoyang, Tinka, Andrew, Kiesel, Scott, Durham, Joseph W., Kumar, T. K. Satish, Koenig, Sven
Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where agents are constantly engaged with new goal locations, such as in large-
Externí odkaz:
http://arxiv.org/abs/2005.07371
Autor:
Bassman, Lindsay, Gulania, Sahil, Powers, Connor, Li, Rongpeng, Linker, Thomas, Liu, Kuang, Kumar, T. K. Satish, Kalia, Rajiv K., Nakano, Aiichiro, Vashishta, Priya
Publikováno v:
Quantum Sci. Technol. 6, 014007 (2020)
Simulation of the dynamics of quantum materials is emerging as a promising scientific application for noisy intermediate-scale quantum (NISQ) computers. Due to their high gate-error rates and short decoherence times, however, NISQ computers can only
Externí odkaz:
http://arxiv.org/abs/2004.07418
In this paper, we study the one-shot and lifelong versions of the Target Assignment and Path Finding problem in automated sortation centers, where each agent needs to constantly assign itself a sorting station, move to its assigned station without co
Externí odkaz:
http://arxiv.org/abs/1912.00253
In multi-agent path finding (MAPF) the task is to navigate agents from their starting positions to given individual goals. The problem takes place in an undirected graph whose vertices represent positions and edges define the topology. Agents can mov
Externí odkaz:
http://arxiv.org/abs/1907.12648
Autor:
Stern, Roni, Sturtevant, Nathan, Felner, Ariel, Koenig, Sven, Ma, Hang, Walker, Thayne, Li, Jiaoyang, Atzmon, Dor, Cohen, Liron, Kumar, T. K. Satish, Boyarski, Eli, Bartak, Roman
The MAPF problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Applications of MAPF include automated w
Externí odkaz:
http://arxiv.org/abs/1906.08291
The Multi-Agent Pickup and Delivery (MAPD) problem models applications where a large number of agents attend to a stream of incoming pickup-and-delivery tasks. Token Passing (TP) is a recent MAPD algorithm that is efficient and effective. We make TP
Externí odkaz:
http://arxiv.org/abs/1812.06355
Autor:
Sartoretti, Guillaume, Kerr, Justin, Shi, Yunfei, Wagner, Glenn, Kumar, T. K. Satish, Koenig, Sven, Choset, Howie
Multi-agent path finding (MAPF) is an essential component of many large-scale, real-world robot deployments, from aerial swarms to warehouse automation. However, despite the community's continued efforts, most state-of-the-art MAPF planners still rel
Externí odkaz:
http://arxiv.org/abs/1809.03531