86 citations · 251 across the 40 of their papers we have counts for
7 papers · 1 filter
Long Horizon Planning through Contact using Discrete Search and Continuous Optimization
Ramkumar Natarajan, Garrison L. H. Johnston, Nabil Simaan +2
Robots often have to perform manipulation tasks in close proximity to people. As such, it is desirable to use a robot arm that has limited joint torques to not injure the nearby pe…
Efficient Recovery Learning using Model Predictive Meta-Reasoning
Shivam Vats, Maxim Likhachev, Oliver Kroemer
Operating under real world conditions is challenging due to the possibility of a wide range of failures induced by execution errors and state uncertainty. In relatively benign sett…
Non-Blocking Batch A* (Technical Report)
Rishi Veerapaneni, Maxim Likhachev
Heuristic search has traditionally relied on hand-crafted or programmatically derived heuristics. Neural networks (NNs) are newer powerful tools which can be used to learn complex…
Effective Integration of Weighted Cost-to-go and Conflict Heuristic within Suboptimal CBS
Rishi Veerapaneni, Tushar Kusnur, Maxim Likhachev
Conflict-Based Search (CBS) is a popular multi-agent path finding (MAPF) solver that employs a low-level single agent planner and a high-level constraint tree to resolve conflicts.…
Synergistic Scheduling of Learning and Allocation of Tasks in Human-Robot Teams
Shivam Vats, Oliver Kroemer, Maxim Likhachev
We consider the problem of completing a set of tasks with a human-robot team using minimum effort. In many domains, teaching a robot to be fully autonomous can be counterproduc…
ePA*SE: Edge-based Parallel A* for Slow Evaluations
Shohin Mukherjee, Sandip Aine, Maxim Likhachev
Parallel search algorithms harness the multithreading capability of modern processors to achieve faster planning. One such algorithm is PA*SE (Parallel A* for Slow Expansions), whi…