クローラロボットの運動学的制約を考慮した視覚慣性自己位置推定
Visual-Inertial Localization for Skid-Steering Robots with Kinematic Constraints
スキッドステアリングロボット向けに、ICRモデルに基づく運動学的制約を視覚慣性SLAMに密結合し、運動パラメータをオンライン推定する低コストな自己位置推定システムを提案した。
著者: Xingxing Zuo, Mingming Zhang, Yiming Chen, Yong Liu, Guoquan Huang, Mingyang Li
分類: cs.RO, cs.CV
原文アブストラクト
While visual localization or SLAM has witnessed great progress in past decades, when deploying it on a mobile robot in practice, few works have explicitly considered the kinematic (or dynamic) constraints of the real robotic system when designing state estimators. To promote the practical deployment of current state-of-the-art visual-inertial localization algorithms, in this work we propose a low-cost kinematics-constrained localization system particularly for a skid-steering mobile robot. In particular, we derive in a principle way the robot's kinematic constraints based on the instantaneous centers of rotation (ICR) model and integrate them in a tightly-coupled manner into the sliding-window bundle adjustment (BA)-based visual-inertial estimator. Because the ICR model parameters are time-varying due to, for example, track-to-terrain interaction and terrain roughness, we estimate these kinematic parameters online along with the navigation state. To this end, we perform in-depth the observability analysis and identify motion conditions under which the state/parameter estimation is viable. The proposed kinematics-constrained visual-inertial localization system has been validated extensively in different terrain scenarios.
