CPU-less robotics: Distributed control of biomorphs

Ralph Etienne-Cummings*, M. Anthony Lewis, Mitra Hartmann, Avis H. Cohen

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Traditional robotics revolves around the microprocessor. All well-known demonstrations of sensory guided motor control, such as jugglers and mobile robots, require at least one CPU. Recently, the availability of fast CPUs have made real-time sensory-motor control possible, however, problems with high power consumption and lack of autonomy still remain. In fact, the best examples of real-time robotics are usually tethered or require large batteries. We present a new paradigm for robotics control that uses no explicit CPU. We use computational sensors that are directly interfaced with adaptive actuation units. The units perform motor control and have learning capabilities. This architecture distributes computation over the entire body of the robot, in every sensor and actuator. Clearly, this is similar to biological sensory-motor systems. Some researchers have tried to model the latter in software, again using CPUs. We demonstrate this idea in with an adaptive locomotion controller chip. The locomotory controller for walking, running, swimming and flying animals is based on a Central Pattern Generator (CPG). CPGs are modeled as systems of coupled non-linear oscillators that control muscles responsible for movement. Here we describe an adaptive CPG model, implemented in a custom VLSI chip, which is used to control an under-actuated and asymmetric robotic leg.

Original languageEnglish (US)
Pages (from-to)83-91
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4109
StatePublished - Dec 1 2000
EventCritical Technologies for the Future of Computing - San Diego, USA
Duration: Jul 31 2000Aug 4 2000

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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