3 accepted papers
With the widespread adoption of robots in high-mix, low-volume manufacturing, and the challenges posed by long-horizon assembly tasks, we introduce the RADAR system—an integrated human-robot collaboration system for Robotic Assembly by Demonstration via Augmented Reality. Existing frameworks lack a…
Most existing 6-DoF robot grasping solutions depend on strong supervision on grasp pose to ensure satisfactory performance, which could be laborious and impractical when the robot works in some restricted area. To this end, we propose a self-supervised 6-DoF grasp pose detection framework via an Aug…
In this work, we present a reinforcement learning algorithm that can find a variety of policies (novel policies) for a task that is given by a task reward function. Our method does this by creating a second reward function that recognizes previously seen state sequences and rewards those by novelty,…