3 accepted papers
This letter introduces an innovative state estimator, MUSE (MUlti-sensor State Estimator), designed to enhance state estimation's accuracy and real-time performance in quadruped robot navigation. The proposed state estimator builds upon our previous work presented in (Fink et al. 2020). It integrate
This letter introduces two multi-sensor state estimation frameworks for quadruped robots, built on the Invariant Extended Kalman Filter (InEKF) and Invariant Smoother (IS). The proposed methods, named E-InEKF and E-IS, fuse kinematics, IMU, LiDAR, and GPS data to mitigate position drift, particularl
Estimation of a quadruped's state is fundamentally important to its operation. In this paper we develop a low-level state estimator for quadrupedal robots that includes attitude, odometry, ground reaction forces, and contact detection. The state estimator is divided into three parts. First, a nonlin…