Zobrazeno 1 - 10
of 1 201
pro vyhledávání: '"A. P. Likhachev"'
Model-based planners and controllers are commonly used to solve complex manipulation problems as they can efficiently optimize diverse objectives and generalize to long horizon tasks. However, they are limited by the fidelity of their model which oft
Externí odkaz:
http://arxiv.org/abs/2410.13979
Graphs of Convex Sets (GCS) is a recent method for synthesizing smooth trajectories by decomposing the planning space into convex sets, forming a graph to encode the adjacency relationships within the decomposition, and then simultaneously searching
Externí odkaz:
http://arxiv.org/abs/2410.08909
Diffusion models have recently been successfully applied to a wide range of robotics applications for learning complex multi-modal behaviors from data. However, prior works have mostly been confined to single-robot and small-scale environments due to
Externí odkaz:
http://arxiv.org/abs/2410.03072
Traditional multi-agent path finding (MAPF) methods try to compute entire start-goal paths which are collision free. However, computing an entire path can take too long for MAPF systems where agents need to replan fast. Methods that address this typi
Externí odkaz:
http://arxiv.org/abs/2410.01798
Robots often face challenges in domestic environments where visual feedback is ineffective, such as retrieving objects obstructed by occlusions or finding a light switch in the dark. In these cases, utilizing contacts to localize the target object ca
Externí odkaz:
http://arxiv.org/abs/2409.18775
Autor:
Veerapaneni, Rishi, Jakobsson, Arthur, Ren, Kevin, Kim, Samuel, Li, Jiaoyang, Likhachev, Maxim
Multi-Agent Path Finding (MAPF) is the problem of effectively finding efficient collision-free paths for a group of agents in a shared workspace. The MAPF community has largely focused on developing high-performance heuristic search methods. Recently
Externí odkaz:
http://arxiv.org/abs/2409.14491
Publikováno v:
IEEE Robotics and Automation Letters, vol. 8, no. 11, pp. 6947-6954, Nov. 2023
In manipulation tasks like plug insertion or assembly that have low tolerance to errors in pose estimation (errors of the order of 2mm can cause task failure), the utilization of touch/contact modality can aid in accurately localizing the object of i
Externí odkaz:
http://arxiv.org/abs/2406.05522
Multi-Robot-Arm Motion Planning (M-RAMP) is a challenging problem featuring complex single-agent planning and multi-agent coordination. Recent advancements in extending the popular Conflict-Based Search (CBS) algorithm have made large strides in solv
Externí odkaz:
http://arxiv.org/abs/2405.01772
The majority of multi-agent path finding (MAPF) methods compute collision-free space-time paths which require agents to be at a specific location at a specific discretized timestep. However, executing these space-time paths directly on robotic system
Externí odkaz:
http://arxiv.org/abs/2404.15137
With the advent of machine learning, there have been several recent attempts to learn effective and generalizable heuristics. Local Heuristic A* (LoHA*) is one recent method that instead of learning the entire heuristic estimate, learns a "local" res
Externí odkaz:
http://arxiv.org/abs/2404.06728