幾何制約を用いたテンセグリティロボットの固有受容状態推定
Tensegrity Robot Proprioceptive State Estimation with Geometric Constraints
3本棒プリズム型テンセグリティ構造の幾何制約とIMU・モータエンコーダから形状・姿勢を再構成し、接触支援不変拡張カルマンフィルタで位置・姿勢を推定する手法を提案した。
著者: Wenzhe Tong, Tzu-Yuan Lin, Jonathan Mi, Yicheng Jiang, Maani Ghaffari, Xiaonan Huang
分類: cs.RO
原文アブストラクト
Tensegrity robots, characterized by a synergistic assembly of rigid rods and elastic cables, form robust structures that are resistant to impacts. However, this design introduces complexities in kinematics and dynamics, complicating control and state estimation. This work presents a novel proprioceptive state estimator for tensegrity robots. The estimator initially uses the geometric constraints of 3-bar prism tensegrity structures, combined with IMU and motor encoder measurements, to reconstruct the robot's shape and orientation. It then employs a contact-aided invariant extended Kalman filter with forward kinematics to estimate the global position and orientation of the tensegrity robot. The state estimator's accuracy is assessed against ground truth data in both simulated environments and real-world tensegrity robot applications. It achieves an average drift percentage of 4.2%, comparable to the state estimation performance of traditional rigid robots. This state estimator advances the state of the art in tensegrity robot state estimation and has the potential to run in real-time using onboard sensors, paving the way for full autonomy of tensegrity robots in unstructured environments.
