Grasp pose estimation in human-robot manipulation tasks using wearable motion sensors

Abstract

Abstract-Knowledge of the human grasp pose is crucial in common control schemes for human-robot object manipulation tasks. Biased estimates of the grasp pose cause undesired interaction wrenches on the human partner, which disturbs the interaction and the recognition of motion intention. A use of wearable motion sensors for tracking the human motion facilitates the grasp pose estimation without a global sensing system. This paper presents an approach for estimating an unknown grasp pose of the human using wearable motion sensors while minimizing undesired interaction wrenches applied to the human. A condition necessary for convergence of the estimator together with appropriate robot motion strategies are provided. Estimation of relative orientation and displacement is performed online and based on minimizing the error in the least-square sense. The estimation process does not rely on a global sensing system and it considers only the measurements of the velocity and acceleration of the cooperating partners in their respective local frames. The approach is experimentally evaluated in a physical human-robot interaction scenario.

Estimating unknown object dynamics in human-robot manipulation tasks

“…According to (6), it can be inferred that zero human wrench, i.e. u h = 0, indicates a zero difference between the desired and actual human pose, i.e.…”

“…Through our previous work [6], it is possible to incorporate online estimation of relative kinematics (quantities in (9)) into the presented approach as well, to account for grasp changes (and/or re-grasping) and slippages of the human hand during interaction.…”

“…The robot and the human rigidly grasp the object, which is assured using the coupling mechanisms at both sides, and additional metal pieces for mounting the coupling mechanisms to the object. T ; the estimation of relative kinematics, however, can also be incorporated through [6]. The interaction wrenches of both the human and the robot are measured by the 6 DoF JR3 force/torque sensors.…”

“…Any bias in the object dynamic parameters, i.e. mass, center of mass, and moments of inertia, results in incorrectly calculated robot wrenches, which may disturb the human during interaction or when performing a desired motion [6], and may affect the trust and interaction behavior of the human partner. Furthermore, biased wrenches D.Ćehajić, P. Budde gen. Dohmann, and S. Hirche are with the Chair of Information-oriented Control, Technical University of Munich, Germany.…”

“…There are a few unique challenges arising in parameter estimation in pHRI: (i) the human is usually unaware of the required motion for identification, (ii) the robot solely executing the identification-relevant motion may cause undesired human wrenches and may disturb the human partner, (iii) the desired estimation strategy needs to account for the human presence by simultaneously allowing the human partner to perform a desired motion while inducing an identification-relevant motion, necessary for parameter convergence. Our previous work [6] considers the estimation of relative kinematics in pHRI by generating a robot motion for identification around the pose of the human wrist, resulting in minimal human interaction forces. However, only a particular case of static human motion is considered and, in addition, object dynamics need to be incorporated.…”