Sensor data fusion for body state estimation in a hexapod robot with dynamical gaits

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Abstract

We report on progress toward a continuous time full 6 DOF translational body state estimator for a hexapod robot executing a jogging gait (with 4 consecutive phases: tripod stance, liftoff transient, aerial, and touchdown transient) on level ground. We use a sequence of dynamical models imported into a standard Kalman Filter to fuse measurements from a novel leg pose sensor and a conventional inertial measurement unit. We implement this estimation procedure on the hexapod robot RHex and evaluate its performance using a visual ground truth measurement system. We also compare the relative performance of different fusion approaches implemented via different model sequences. © 2005 IEEE.

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APA

Lin, P. C., Komsuglu, H., & Koditschek, D. E. (2005). Sensor data fusion for body state estimation in a hexapod robot with dynamical gaits. In Proceedings - IEEE International Conference on Robotics and Automation (Vol. 2005, pp. 4733–4738). https://doi.org/10.1109/ROBOT.2005.1570851

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