Abstract
We report on a sensor data fusion algorithm via an extended Kalman filter for estimating the spatial motion of a bipedal robot. Through fusing the sensory information from joint encoders, a 6-axis inertial measurement unit and a 2-axis inclinometer, the robot’s body state at a specific fixed position can be yielded. This position is also equal to the CoM when the robot is in the standing posture suggested by the detailed CAD model of the robot. In addition, this body state is further utilized to provide sensory information for feedback control on a bipedal robot with walking gait. The overall control strategy includes the proposed body state estimator as well as the damping controller, which regulates the body position state of the robot in real-time based on instant and historical position tracking errors. Moreover, a posture corrector for reducing unwanted torque during motion is addressed. The body state estimator and the feedback control structure are implemented in a child-size bipedal robot and the performance is experimentally evaluated.
Highlights
Due to the rapid growth in robotics in recent decades, it is unavoidable that robots should come into our lives, interacting with us and the environment
In order to grant walking stability to the bipedal robots, the implementation of a real-time feedback controller is crucial to deal with the uncertainty and disturbance from the outside, and the controller usually relies on the sensory information of the body state or ground reaction forces
To evaluate the performance of the body state estimator, the robot walked within the ground truth measurement system (GTMS) 5 times and its leg joints were operated according to the nominal center of mass (CoM)
Summary
Due to the rapid growth in robotics in recent decades, it is unavoidable that robots should come into our lives, interacting with us and the environment. A full body state estimation algorithm was proposed based on IMU and legged odometry for a quadruped [10] An. IMU/encoder fusion model-based feedback control was developed for improving the stability of the robot’s jogging motion [18]. In order to grant walking stability to the bipedal robots, the implementation of a real-time feedback controller is crucial to deal with the uncertainty and disturbance from the outside, and the controller usually relies on the sensory information of the body state or ground reaction forces.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
