In this work, we present a highly functional teleoperation system, that integrates a full-body inertia-based motion capture suit and three intuitive teleoperation strategies with a Whole-Body Control (WBC) framework, for quadrupedal legged manipulators. This enables the realisation of commands from the teleoperator that would otherwise not be possible, as the framework is able to utilise DoF redundancy to meet several objectives simultaneously, such as locking the gripper frame in position while the trunk completes a task. This is achieved through the WBC framework featuring a defined optimisation problem that solves a range of Cartesian and joint space tasks, while subject to a set of constraints (e.g. halt constraints). These tasks and constraints are highly modular and can be configured dynamically, allowing the teleoperator to switch between teleoperation strategies seamlessly. The overall system has been tested and validated through a physics-based simulation and a hardware test, demonstrating all functionality of the system, which in turn has been used to evaluate its effectiveness.
This article presents a standardized human-robot teleoperation interface (HRTI) evaluation scheme for mobile manipulators. Teleoperation remains the predominant control type for mobile manipulators in open environments, particularly for quadruped manipulators. However, mobile manipulators, especially quadruped manipulators, are relatively novel systems to be implemented in the industry compared to traditional machinery. Consequently, no standardized interface evaluation method has been established for them. The proposed scheme is the first of its kind in evaluating mobile manipulator teleoperation. It comprises a set of robot motion tests, objective measures, subjective measures, and a prediction model to provide a comprehensive evaluation. The motion tests encompass locomotion, manipulation, and a combined test. The duration for each trial is collected as the response variable in the objective measure. Statistical tools, including mean value, standard deviation, and T-test, are utilized to cross-compare between different predictor variables. Based on an extended Fitts' law, the prediction model employs the time and mission difficulty index to forecast system performance in future missions. The subjective measures utilize the NASA-task load index and the system usability scale to assess workload and usability. Finally, the proposed scheme is implemented on a real-world quadruped manipulator with two widely-used HRTIs, the gamepad and the wearable motion capture system.
This paper presents a motion-capture based control framework for the purpose of effectively teleoperating two legged manipulators without significant delays caused by the switching of controllers. The control framework generates high-level trajectories in 6 degrees-of-freedom and uses finger gesture detection to act as triggers in selecting which robot to control as well as toggling various aspects of control such as yaw rotation of the quadruped platform. The functionality and ease of use of the control framework is demonstrated through a real life experiment where the operator controls two quadrupedal manipulator robots to open a spray can. The experiment was successfully accomplished by the proposed teleoperation framework.
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