Evaluation of a Large Scale Event Driven Robot Skin

Florian Bergner, Emmanuel Dean-Leon, Julio Rogelio Guadarrama-Olvera, Gordon Cheng

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This letter evaluates and describes the large-scale integration of our multi-modal event-driven robot skin system on our humanoid robot H1 (REEM-C, PAL robotics). The robot skin is powered by the robot and all processing of tactile perception and control are executed onboard the robot. The robot skin system largely covers the humanoid and employs 1260 skin cells in 47 skin patches, in total 7560 multi-modal tactile sensors. The robot skin system is driven by events, i.e., the occurrence of novel information drives the acquisition, transmission, and processing of information rather than the synchronous sampling clock as in clock-driven systems. The event-driven robot skin system enables efficient multi-modal large area tactile perception, which is a prerequisite for realizing reactive whole-body control. We analyze the new robot skin system and evaluate its performance in clock-driven mode and event-driven mode. This analysis includes modeling the required CPU load and investigating the scaling of the system in multi-core systems. We evaluate the robot skin system with an experiment, where a large number of skin cells is activated ($>$680 cells), and a large number of events is generated. The obtained results demonstrate the superior performance of the event-driven system. In the clock-driven mode, the robot skin system constantly produces 315 000 packets/s, while in event-driven mode the system at most produces 40 000 packets/s (13%). The CPU load reduces from constantly 270% to at most 100% (37%). In clock-driven mode, the PC drops on average 80 000 packets/s (25% of all packets), while in event-driven mode, the package loss is practically neglectable. This efficient large-scale robot skin enables the complete onboard integration into a humanoid robot without the need for additional external power or processing capabilities.

Original languageEnglish
Article number8769940
Pages (from-to)4247-4254
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume4
Issue number4
DOIs
StatePublished - Oct 2019

Keywords

  • Force and Tactile Sensing
  • Humanoid Robots

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