Slope angle estimation based on multi-sensor fusion for a snake-like robot

Zhenshan Bing, Long Cheng, Alois Knoll, Anyang Zhong, Kai Huang, Feihu Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

In this paper, we report on a body state and ground profile estimator for a snake-like robot executing a rolling gait to travel from flat ground to a slope. With the help of the estimator, the snake-like robot can adaptively adjust the body shape and locomotion speed by changing the gait parameters for the purpose of tackling a steep slope. Specifically, we propose a repeating sequence of continuous time dynamical models to fuse kinematic encoder data with on-board Inertial Measurement Unit (IMU) measurements based on extended Kalman filter (EKF). All the sensors are mounted inside each module of the snake-like robot, which measure the joint position, the three-axis acceleration, and the three-axis angular velocity. Further, the robot changes its moving pattern under our policy, judging by the estimated angle of the ground profile. We implement this estimation procedure off-line, using data extracted from repeated runs of the snake-like robot by simulation and evaluate its performance compared to the ground truth.

Original languageEnglish
Title of host publication20th International Conference on Information Fusion, Fusion 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780996452700
DOIs
StatePublished - 11 Aug 2017
Event20th International Conference on Information Fusion, Fusion 2017 - Xi'an, China
Duration: 10 Jul 201713 Jul 2017

Publication series

Name20th International Conference on Information Fusion, Fusion 2017 - Proceedings

Conference

Conference20th International Conference on Information Fusion, Fusion 2017
Country/TerritoryChina
CityXi'an
Period10/07/1713/07/17

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