Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Abstract

Legged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

Graphical abstract

Keywords

terrain classification / hexapod robot / legged robot / adaptive locomotion / gait control

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Acknowledgements

This work was supported by the National Nature Science Foundation of China (Grant Nos. U1613208 and 51927809), the National Key R&D Program of China (Grant No. 2017YFE0112200), and the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska–Curie grant (Grant No. 734575).

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