565 citations · 844 across the 22 of their papers we have counts for
9 papers · 1 filter
A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance
Andrea Bajcsy, Sylvia L. Herbert, David Fridovich-Keil +4
Robust motion planning is a well-studied problem in the robotics literature, yet current algorithms struggle to operate scalably and safely in the presence of other moving agents,…
Safely Probabilistically Complete Real-Time Planning and Exploration in Unknown Environments
David Fridovich-Keil, Jaime F. Fisac, Claire J. Tomlin
We present a new framework for motion planning that wraps around existing kinodynamic planners and guarantees recursive feasibility when operating in a priori unknown, static envir…
Learning under Misspecified Objective Spaces
Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac +1
Learning robot objective functions from human input has become increasingly important, but state-of-the-art techniques assume that the human's desired objective lies within the rob…
Hierarchical Game-Theoretic Planning for Autonomous Vehicles
Jaime F. Fisac, Eli Bronstein, Elis Stefansson +3
The actions of an autonomous vehicle on the road affect and are affected by those of other drivers, whether overtaking, negotiating a merge, or avoiding an accident. This mutual de…
A Minimum Discounted Reward Hamilton-Jacobi Formulation for Computing Reachable Sets
Anayo K. Akametalu, Shromona Ghosh, Jaime F. Fisac +1
We propose a novel formulation for approximating reachable sets through a minimum discounted reward optimal control problem. The formulation yields a continuous solution that can b…
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac +3
Our goal is for AI systems to correctly identify and act according to their human user's objectives. Cooperative Inverse Reinforcement Learning (CIRL) formalizes this value alignme…