A Novel Foot Contact Probability Estimator for Biped Robot State Estimation

State estimation is an important part of biped robot control, but unreliable foot contact estimation would lead to inaccurate state estimation result. In this paper, to reduce the state estimation error caused by the inaccurate contact estimation, we propose a novel simplified contact probability estimator based on the force/torque sensor mounted on the foot. The contact probability is used to tune the covariance matrices of the extended Kalman filter, and the parameters of the probability estimator are optimized iteratively through minimizing the error between state estimation result and ground truth measurement. The experimental result on BHR-6P biped robot shows that the proposed method can effectively reduce the state estimation error.

[1]  Danica Kragic,et al.  Online contact point estimation for uncalibrated tool use , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[2]  Nicholas Rotella,et al.  Unsupervised Contact Learning for Humanoid Estimation and Control , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[3]  Xuechao Chen,et al.  Contact Force/Torque Control Based on Viscoelastic Model for Stable Bipedal Walking on Indefinite Uneven Terrain , 2019, IEEE Transactions on Automation Science and Engineering.

[4]  Olivier Stasse,et al.  Experimental evaluation of simple estimators for humanoid robots , 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).

[5]  Danna Zhou,et al.  d. , 1934, Microbial pathogenesis.

[6]  Seth J. Teller,et al.  Drift-free humanoid state estimation fusing kinematic, inertial and LIDAR sensing , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[7]  Darwin G. Caldwell,et al.  Probabilistic Contact Estimation and Impact Detection for State Estimation of Quadruped Robots , 2017, IEEE Robotics and Automation Letters.

[8]  Nima Fazeli,et al.  Parameter and contact force estimation of planar rigid-bodies undergoing frictional contact , 2017, Int. J. Robotics Res..

[9]  Neil Genzlinger A. and Q , 2006 .

[10]  Aaron D. Ames,et al.  Dynamic Walking with Compliance on a Cassie Bipedal Robot , 2019, 2019 18th European Control Conference (ECC).

[11]  Scott Kuindersma,et al.  A Constrained Kalman Filter for Rigid Body Systems with Frictional Contact , 2018, WAFR.

[12]  Nicholas Rotella,et al.  State estimation for a humanoid robot , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Peter Fankhauser,et al.  Probabilistic foot contact estimation by fusing information from dynamics and differential/forward kinematics , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[14]  Stylianos Piperakis,et al.  Unsupervised Gait Phase Estimation for Humanoid Robot Walking* , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[15]  Nando de Freitas,et al.  Taking the Human Out of the Loop: A Review of Bayesian Optimization , 2016, Proceedings of the IEEE.

[16]  Cameron Patrick Ridgewell Humanoid Robot Friction Estimation in Multi-Contact Scenarios , 2017 .

[17]  Maani Ghaffari Jadidi,et al.  Contact-Aided Invariant Extended Kalman Filtering for Legged Robot State Estimation , 2018, Robotics: Science and Systems.

[18]  Axel Barrau,et al.  The Invariant Extended Kalman Filter as a Stable Observer , 2014, IEEE Transactions on Automatic Control.

[19]  W. Marsden I and J , 2012 .

[20]  Simon J. Julier,et al.  Weak in the NEES?: Auto-Tuning Kalman Filters with Bayesian Optimization , 2018, 2018 21st International Conference on Information Fusion (FUSION).

[21]  Roland Siegwart,et al.  State Estimation for Legged Robots - Consistent Fusion of Leg Kinematics and IMU , 2012, Robotics: Science and Systems.

[22]  Roland Siegwart,et al.  State estimation for legged robots on unstable and slippery terrain , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Maani Ghaffari Jadidi,et al.  Legged Robot State-Estimation Through Combined Forward Kinematic and Preintegrated Contact Factors , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[24]  Christopher G. Atkeson,et al.  Dynamic state estimation using Quadratic Programming , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.