Title
Efficient event-driven reactive control for large scale robot skin
Abstract
In this work we present a novel efficient event-driven reactive skin controller for large scale robot skin. The novel event-driven controller derives from a standard Jacobian torque controller and fully takes advantage of our multi-modal event-driven robot skin. Event-driven systems only sample, transmit and process information when the novelty of the information is guaranteed. This increases their efficiency in comparison to synchronous systems. We also use the new event-driven controller formulation to design a new synchronous reactive skin controller. We compare both controllers in a comprehensive performance evaluation with our robot TOMM. TOMM has two UR5 robot arms, each covered with 253 multi-modal skin cells. Each skin cell samples 4 different modalities and supports data mode and event mode. The results show that the event-driven reactive skin controller always outperforms the synchronous reference controller while both controllers show exactly the same response. When the robot is not moving then the event-driven controller reduces the CPU usage by 78% in comparison to the synchronous reference controller. When the robot is responding to contacts then the CPU usage reduces by 66%.
Year
DOI
Venue
2017
10.1109/ICRA.2017.7989051
2017 IEEE International Conference on Robotics and Automation (ICRA)
Keywords
Field
DocType
large-scale robot skin,efficient event-driven reactive skin controller,standard Jacobian torque controller,multimodal event-driven robot skin,synchronous reactive skin controller design,robot TOMM,UR5 robot arms,multimodal skin cells,CPU usage reduction
Robot control,Control theory,Central processing unit,Torque,Jacobian matrix and determinant,Control theory,Simulation,Robot kinematics,Control engineering,Engineering,Robot,Open-loop controller
Conference
Volume
Issue
ISBN
2017
1
978-1-5090-4634-8
Citations 
PageRank 
References 
3
0.41
18
Authors
3
Name
Order
Citations
PageRank
Florian Bergner1216.14
Emmanuel C. Dean-Leon26215.39
Gordon Cheng31250115.33