Title
Adaptive Compliance Control Of A Multi-Legged Stair-Climbing Robot Based On Proprioceptive Data
Abstract
Purpose - The purpose of this paper is to describe an innovative compliance control architecture for hybrid multi-legged robots. The approach was verified on the hybrid legged-wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters.Design/methodology/approach - The paper shows how this adaptivity results in a versatile controller for hybrid legged-wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA-based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair-climbing capabilities.Findings - The robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust-proof corpus and the ability to swim are additional features of the robot.Originality/value - Contrary to existing approaches, a pre-defined walking pattern for stair-climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on-line.
Year
DOI
Venue
2009
10.1108/01439910910957084
INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION
Keywords
Field
DocType
Adaptive system theory, Control systems, Robotics
Urban search and rescue,Robot control,Control theory,Simulation,Situation awareness,Control engineering,Artificial intelligence,Control system,Engineering,Stair climbing,Robot,Robotics
Journal
Volume
Issue
ISSN
36
4
0143-991X
Citations 
PageRank 
References 
1
0.40
1
Authors
3
Name
Order
Citations
PageRank
Markus Eich1313.63
Felix Grimminger21048.08
Frank Kirchner314324.53