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Paper TuA09.3

Flacco, Fabrizio (UniversitÓ di Roma "La Sapienza"), Kroeger, Torsten (Stanford University), De Luca, Alessandro (UniversitÓ di Roma "La Sapienza"), Khatib, Oussama (Stanford University)

A Depth Space Approach to Human-Robot Collision Avoidance

Scheduled for presentation during the Regular Session "Collision" (TuA09), Tuesday, May 15, 2012, 09:00−09:15, Meeting Room 9 (Sa)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on February 23, 2018

Keywords Collision Avoidance, Physical Human-Robot Interaction, Visual Servoing

Abstract

In this paper a real-time collision avoidance approach is presented for safe human-robot coexistence. The main contribution is a fast method to evaluate distances between the robot and possibly moving obstacles (including humans), based on the concept of depth space. With these distances, repulsive vectors are generated that are used to control the robot while executing a generic motion task. The repulsive vectors can also take advantage of an estimation of the obstacle velocity. In order to preserve the execution of a Cartesian task with a redundant manipulator, a simple collision avoidance algorithm has been implemented where different reaction behaviors are set up for the end-effector and for other control points along the robot structure. The complete collision avoidance framework, from perception of the environment to joint-level robot control, is presented for a 7-dof KUKA Light-Weight-Robot IV using the Microsoft Kinect sensor. Experimental results are reported for dynamic environments with obstacles and a human.

 

 

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