2018/09/10 by Luis Contreras, H. Yokoyama, Contreras, Luis +3
Computer Science · Engineering · #FOS: Computer and information sciences #Robot Manipulation and Learning #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization
paper · pdf · doi:10.48550/arxiv.1809.03216
openalex publication_date 2018/09/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this work, we present a multimodal system for active robot-object interaction using laser-based SLAM, RGBD images, and contact sensors. In the object manipulation task, the robot adjusts its initial pose with respect to obstacles and target objects through RGBD data so it can perform object grasping in different configuration spaces while avoiding collisions, and updates the information related to the last steps of the manipulation process using the contact sensors in its hand. We perform a series of experiment to evaluate the performance of the proposed system following the the RoboCup2018 international competition regulations. We compare our approach with a number of baselines, namely a no-feedback method and visual-only and tactile-only feedback methods, where our proposed visual-and-tactile feedback method performs best.