7 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 many autonomous mapping tasks, the maps cannot be accurately constructed due to various reasons such as sparse, noisy, and partial sensor measurements. We propose a novel map prediction method built upon recent success of Low-Rank Matrix Completion. The proposed map prediction is able to achieve…
This paper studies the problem of autonomous exploration under localization uncertainty for a mobile robot with 3D range sensing. We present a framework for self-learning a high-performance exploration policy in a single simulation environment, and transferring it to other environments, which may be…
We consider an autonomous mapping and exploration problem in which a range-sensing mobile robot is guided by an information-based controller through an a priori unknown environment, choosing to collect its next measurement at the location estimated to yield the maximum information gain within its cu…
We present a novel approach to perform underwater simultaneous localization and mapping (SLAM) using a small inspection-class remotely operated vehicle (ROV) equipped with a single-beam scanning sonar, amidst high levels of noise present in the sonar data, and in the absence of inertial/odometry mea…
We consider an autonomous exploration problem in which a mobile robot is guided by an information-based controller through an a priori unknown environment, choosing to collect its next measurement at the location estimated to be most informative within its current field of view. We propose a novel a…