Operation Planning and Closed-Loop Control of a Soft Robotic Table for Simultaneous Multiple-Object Manipulation

摘要

This article presents the design, development, and validation of a closed-loop control system for a soft robotic table. The soft table can provide independent manipulation to multiple objects simultaneously, which is an advantage over traditional devices such as robotic arms and belt conveyor systems. The table also provides intrinsic soft handling for delicate objects. In order to execute automation tasks, a vision feedback system and an operation controller are developed and incorporated into the existing table prototype to form a closed-loop control. The vision feedback system implements image processing techniques to identify the object location from captured images. The operation controller is integrated from three sets of algorithms, including movement planning, actuator selection, and actuation planning. Two sets of experiments were conducted to validate the closed-loop system and the capability of the soft table. The first set validated the manipulation task of transporting an object to a desired location with autonomous planning and execution. The second set validated the table's ability to manipulate multiple objects simultaneously and independently. Videos of both experiments have been supplied.