1 citations · 1 across the 5 of their papers we have counts for
7 papers
Evaluating the Effectiveness of Corrective Demonstrations and a Low-Cost Sensor for Dexterous Manipulation
Abhineet Jain, Jack Kolb, J. M. Abbess +1
Imitation learning is a promising approach to help robots acquire dexterous manipulation capabilities without the need for a carefully-designed reward or a significant computationa…
Desperate Times Call for Desperate Measures: Towards Risk-Adaptive Task Allocation
Max Rudolph, Sonia Chernova, Harish Ravichandar
Multi-robot task allocation (MRTA) problems involve optimizing the allocation of robots to tasks. MRTA problems are known to be challenging when tasks require multiple robots and t…
An Interleaved Approach to Trait-Based Task Allocation and Scheduling
Glen Neville, Andrew Messing, Harish Ravichandar +2
To realize effective heterogeneous multi-robot teams, researchers must leverage individual robots' relative strengths and coordinate their individual behaviors. Specifically, heter…
Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization
Abhinav Jain, Daphne Chen, Dhruva Bansal +6
We address the problem of adapting robot trajectories to improve safety, comfort, and efficiency in human-robot collaborative tasks. To this end, we propose CoMOTO, a trajectory op…
Taking Recoveries to Task: Recovery-Driven Development for Recipe-based Robot Tasks
Siddhartha Banerjee, Angel Daruna, David Kent +9
Robot task execution when situated in real-world environments is fragile. As such, robot architectures must rely on robust error recovery, adding non-trivial complexity to highly-c…
Inferring and Learning Multi-Robot Policies by Observing an Expert
Pietro Pierpaoli, Harish Ravichandar, Nicholas Waytowich +3
We present a technique for learning how to solve a multi-robot mission that requires interaction with an external environment by observing an expert system executing the same missi…