29 citations · 34 across the 5 of their papers we have counts for
5 papers
Trajectory Planning with Deep Reinforcement Learning in High-Level Action Spaces
Kyle R. Williams, Rachel Schlossman, Daniel Whitten +8
This paper presents a technique for trajectory planning based on continuously parameterized high-level actions (motion primitives) of variable duration. This technique leverages de…
Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report
Rishi Shah, Yuqian Jiang, Haresh Karnan +8
RoboCup@Home is an international robotics competition based on domestic tasks requiring autonomous capabilities pertaining to a large variety of AI technologies. Research challenge…
Toward Achieving Formal Guarantees for Human-Aware Controllers in Human-Robot Interactions
Rachel Schlossman, Minkyu Kim, Ufuk Topcu +1
With the primary objective of human-robot interaction being to support humans' goals, there exists a need to formally synthesize robot controllers that can provide the desired serv…
Decentralized Control Systems Laboratory Using Human Centered Robotic Actuators
Binghan He, Kunye Chen, Rachel Schlossman +5
University laboratories deliver unique hands-on experimentation for STEM students but often lack state-of-the-art equipment and provide limited access to their equipment. The Unive…
Exploiting the Natural Dynamics of Series Elastic Robots by Actuator-Centered Sequential Linear Programming
Rachel Schlossman, Gray C. Thomas, Orion Campbell +1
Series elastic robots are best able to follow trajectories which obey the limitations of their actuators, since they cannot instantly change their joint forces. In fact, the perfor…