Combining haptics and inertial motion capture to enhance remote control of a dual-arm robot

High dexterity is required in tasks in which there is contact between objects, such as surface conditioning (wiping, polishing, scuffing, sanding, etc.), specially when the location of the objects involved is unknown or highly inaccurate because they are moving, like a car body in automotive industry lines. These applications require the human adaptability and the robot accuracy. However, sharing the same workspace is not possible in most cases due to safety issues. Hence, a multi-modal teleoperation system combining haptics and an inertial motion capture system is introduced in this work. The human operator gets the sense of touch thanks to haptic feedback, whereas using the motion capture device allows more naturalistic movements. Visual feedback assistance is also introduced to enhance immersion. A Baxter dual-arm robot is used to offer more flexibility and manoeuvrability, allowing to perform two independent operations simultaneously. Several tests have been carried out to assess the proposed system. As it is shown by the experimental results, the task duration is reduced and the overall performance improves thanks to the proposed teleoperation method.

Robust Control of a New Asymmetric Teleoperation Robot Based on a State Observer

This study is mainly about the designation of a new type of haptic device and an asymmetric teleoperation robot system. Aiming at the problems of tracking and transparency of an asymmetric teleoperation system, a robust control algorithm based on a state observer was proposed. The Haptic Device was designed and was chosen as the master-robot of the system. The Baxter dual-arm robot was chosen as the slave-robot of the system. The simulation experiment of robust control based on a state observer of the asymmetric teleoperation robot was carried out. The experiment results showed that the maximum values of displacement tracking errors in three directions x, y, and z are 0.02 m, 0.01 m, and 0.015 m, respectively. Compared with single- joint PID control, the performance of the new control algorithm is improved. The force feedback experiment on the real asymmetric teleoperation robot system was carried out. The results showed that the force feedback wave is consistent with the actual situation and showed that the robust control algorithm proposed is superior to PID. Therefore, the algorithm perfectly satisfied the system. The experiment parameters also demonstrate that the haptic device satisfies the design requirements of the asymmetric teleoperation robots system and the industry standards.

Research on Input Scheme Selection of a Novel Parallel Mechanism

When the two arms of the robot are transporting the heavy loads together, a new parallel mechanism is formed. The actuator input selection and optimization of the parallel mechanism are basic and important problems in mechanism research. In this paper, a 2-RPPPS dual-arm robot is taken as the research object. Firstly, based on the screw theory and input selection principle, 158 reasonable schemes are obtained. Then, an evaluation mechanism is established to screen out the schemes that do not conform to the input selection principle. Then, the end effector of the parallel mechanism moves along two different trajectories. Using the particle swarm optimization algorithm, the inverse kinematics solution of each trajectory is obtained, and the velocity and acceleration of each actuator under different trajectories are obtained. Finally, the motion stability of each actuator is evaluated, and the best scheme is selected. The results show that the best input scheme can be selected according to different trajectories, so as to improve the performance of the parallel mechanism. To the authors’ knowledge, no one has done any research on selecting the appropriate input scheme according to the trajectory of the end effector.