3 papers
cs.RO2021
Chance-Constrained Motion Planning using Modeled Distance-to-Collision Functions
Jacob J. Johnson, Michael C. Yip
This paper introduces Chance Constrained Gaussian Process-Motion Planning (CCGP-MP), a motion planning algorithm for robotic systems under motion and state estimate uncertainties.…
cs.RO2020
Dynamically Constrained Motion Planning Networks for Non-Holonomic Robots
Jacob J. Johnson, Linjun Li, Fei Liu +2
Reliable real-time planning for robots is essential in today's rapidly expanding automated ecosystem. In such environments, traditional methods that plan by relaxing constraints be…
cs.LG2019
Composing Task-Agnostic Policies with Deep Reinforcement Learning
Ahmed H. Qureshi, Jacob J. Johnson, Yuzhe Qin +3
The composition of elementary behaviors to solve challenging transfer learning problems is one of the key elements in building intelligent machines. To date, there has been plenty…