A constraint-based approach for human–robot collision avoidance. (3rd March 2020)

• Record Type: Journal Article
• Authors: Mronga, Dennis; Knobloch, Tobias; de Gea Fernández, José; Kirchner, Frank
• Is Part Of: Advanced robotics. Volume 34:Number 5(2020)
• Page Start: 265
• Page End: 281
• Publication Date: 2020-03-03
• Subjects: Collision avoidance -- human–robot collaboration -- real-time robot control -- parameter optimization; Robotics -- Periodicals; Robotics -- Japan -- Periodicals; Robotics; Japan; Periodicals; 629.89205
• DOI: 10.1080/01691864.2020.1721322
• Languages: English
• ISSNs: 0169-1864

Abstract

Abstract : In this paper, we present a software-based approach for collision avoidance that can be applied in human–robot collaboration scenarios. One of the contributions is a method for converting clustered 3D sensor data into computationally efficient convex hull representations used for robot-obstacle distance computation. Based on the computed distance vectors, we generate collision avoidance motions using a potential field approach and integrate them with other simultaneously running robot tasks in a constraint-based control framework. In order to improve control performance, we apply evolutionary techniques for parameter optimization within this framework based on selected quality criteria. Experiments are performed on a dual-arm robotic system equipped with several depth cameras. The approach is able to generate task-compliant avoidance motions in dynamic environments with high performance. GRAPHICAL ABSTRACT: