テンセグリティロボットの状態推定
State Estimation for Tensegrity Robots
テンセグリティロボット向けに、慣性計測・UWB測距・アクチュエータ情報を統合したアンセンテッドカルマンフィルタによる状態推定器を設計し、惑星探査プロトタイプSUPERballで評価した論文。
著者: Ken Caluwaerts, Jonathan Bruce, Jeffrey M. Friesen, Vytas SunSpiral
分類: cs.RO
原文アブストラクト
Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robot's success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.
