A task-space weighting matrix approach to semi-autonomous teleoperation control

Abstract

A semi-autonomous control strategy is proposed for teleoperation of a mobile base and/or a twin-arm robotic manipulator for use when conventional teleoperation is inadequate. The approach employs idempotent and generalized pseudoinverse matrices to augment operator(s) control with some level of assistance/autonomy. An application specific task-space weighting matrix is introduced to adjust the relative weight of autonomous control with respect to human-centered teleoperation control. The task-space weighting matrix allows for a smooth continuous transition from completely autonomous to shared control, and to completely human teleoperated control. Experiments with a twin-armed mobile slave robot demonstrate the feasibility and basic functionality of the controller.

Task Performance Evaluation of Asymmetric Semiautonomous Teleoperation of Mobile Twin-Arm Robotic Manipulators

“…The first mode denoted as no assistance (NA) did not utilize any semiautonomous control. This was accomplished by setting w c ¼ 0 in the teleoperation task-space weighting matrix [17]. The remaining modes employed different soft constraints by having w c attain a maximum value of one when the soft constraint was at its maximum strength.…”

“…1c. The control is based on the semiautonomous approach from [17]. In this method, position tracking remains as one of the transparency properties, i.e., k ip x im ¼ x is for i ¼ 1; 2.…”

“…In this method, position tracking remains as one of the transparency properties, i.e., k ip x im ¼ x is for i ¼ 1; 2. Passive assistance is provided via the "soft" velocity-constraints [17]. The "soft" constraints on the slave robotic arms are formulated based on their "hard" counterparts, i.e.,…”

“…In this paper, the authors newly developed methods for trilateral teleoperation [5], [4], teleoperation of nonholonomic mobile robots [4], and semiautonomous grasping assistance in dual-slave teleoperation [17] are revisited and evaluated from an operator performance perspective. These different control approaches are special cases of a more general and systematic control strategy for hapticenabled AST systems presented in [3] that is ultimately applied for teleoperation of a mobile twin-arm robot manipulator.…”

Teleoperation of a mobile robot with model-predictive obstacle avoidance control

“…The main contribution of this work is the development of an MPC-based obstacle avoidance algorithm and its integration within the general mixed autonomous/teleoperation control framework in [23] and [24] to provide the operator with corrective force feedback. This generalized framework covers various possible system configurations and builds on the earlier work in [25], [26]. Among the different configurations considered in [23], [24], this work particularly formulates the collision avoidance as an autonomous subtask using the Single-Master Single-Slave (SMSS) teleoperation configuration.…”