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Radar Based Target Tracking and Classification for Efficient Robot Speed Control in Fenceless Environments

Barnaba Ubezio, Christian Schöffmann, Lucas Wohlhart, Stephan Mulbacher-Karrer, Hubert Zangl, Michael Hofbaur

Year
2021
Citations
12

Abstract

Awareness of its surroundings is a crucial capability for a robot meant to be working alongside other robots or human operators. When considering safety norms and modalities, in particular the Speed and Separation Monitoring (SSM), proper proximity information can make the difference in the overall efficiency of a use case, for example avoiding unnecessary penalizations in the cycle-time. This paper presents a method to exploit the proximity perception capabilities of radar sensors to construct a continuous speed control algorithm for a UR10 robot. With respect to standard implementations of the SSM in industrial and collaborative environments, the proposed speed control is enhanced by the addition of direct human’s velocity measurement, full direction of travel and target classification. The results are evalauted according to the SSM metrics for safety and productivity, showing an overall increase in efficiency while still maintaining safety level requirements.

Keywords

RobotComputer scienceRadarExploitConstruct (python library)ImplementationSeparation (statistics)Artificial intelligenceAutomationMobile robot

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