ANYmal at the ARGOS Challenge: Tools and Experiences from the Autonomous Inspection of Oil &amp; Gas Sites with a Legged Robot

Fankhauser, Péter; Gehring, Christian; Diethelm, Remo; Bachmann, S.; Bellicoso, C. Dario; Wermelinger, Martin; Tsounis, Vasilios; Bloesch, Michael; Leemann, Philipp; Hottiger, Gabriel; Lauber, Andreas; Jud, Dominik; Kaestner, Ralf; Hoepflinger, Mark A.; Hutter, Marco

doi:10.36288/roscon2016-900219

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“…The DARPA Robotics Challenge program conducted a series of competition events to develop and demonstrate technology for disaster response [1]. The Argos Challenge is a robotic challenge in the oil and gas industry sponsored by TOTAL [2]. Although many robots perform well in these kinds of competitions, most of them are wheeled or tracked robots.…”

Section: Introductionmentioning

confidence: 99%

Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

et al. 2021

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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.

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Section: Introductionmentioning

confidence: 99%