Neural Control with an Artificial Hormone System for Energy-Efficient Compliant Terrain Locomotion and Adaptation of Walking Robots

Conference proceedings article

Authors/Editors

PITIWUT TEERAKITTIKUL

Strategic Research Themes

No matching items found.

Publication Details

Author list: Homchanthanakul J., Ngamkajornwiwat P., Teerakittikul P., Manoonpong P.

Publisher: Institute of Electrical and Electronics Engineers Inc.

Publication year: 2019

Start page: 5475

End page: 5482

Number of pages: 8

ISBN: 9781728140049

ISSN: 2153-0858

eISSN: 2153-0858

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081157057&doi=10.1109%2fIROS40897.2019.8968580&partnerID=40&md5=233aaf0d1001ebbc1f15dc7845bce9f8

Languages: English-Great Britain (EN-GB)

View in Web of Science | View on publisher site | View citing articles in Web of Science

Abstract

In order to use walking robots for exploration in a real complex environment, an adaptive control system is required to allow them to successfully and efficiently traverse the terrains. To achieve this, we propose here our adaptive locomotion control technique of a walking robot. It is based on a modular structure, combining neural control with an artificial hormone system. The neural control coordinates all leg joints of the robot and generates its locomotion with various insect-like gaits. In parallel, the artificial hormone system uses the motor commands from the neural control and foot contact feedback to estimate the walking state and automatically adapt the joint movements with respect to the terrain. The adaptability is quickly achieved in an online manner within a few seconds. Robot walking experiments show that this adaptive control technique enables a six-legged robot to adapt to various difficult terrains with energy efficiency. Such terrains include sand (loose ground), sponge with different softness levels (soft/compliant ground), grass (vegetated ground), and floor/pavement (hard ground). The technique does not require robot kinematics or an environmental model; and can, therefore, be potentially applied to different legged robots to achieve stable online adaptation and energy-efficient locomotion on unpredictable (compliant) terrains. ฉ 2019 IEEE.

Keywords