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

AbstractHigh 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.

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A dual-arm manipulation strategy using position/force errors and Kalman filter

Transactions of the Institute of Measurement and Control ◽

10.1177/01423312211018681 ◽

2021 ◽

pp. 014233122110186

Author(s):

Wu-Te Yang ◽

Bo-Hsun Chen ◽

Pei-Chun Lin

Keyword(s):

Kalman Filter ◽

Force Control ◽

Spatial Relation ◽

Digital Controller ◽

Custom Made ◽

Series Of Experiments ◽

Dual Arm Robot ◽

Sense Of Touch ◽

Dual Arm ◽

Manipulation Strategy

This paper presents a new coordination manipulation strategy for a custom-made dual-arm robot. With master and slave coordination infrastructure, both spatial relation and sense of touch are considered to hold an object stably. Given the known trajectory of the master arm, the slave arm fuses position and force commands by using the Kalman filter to yield optimal compensation amounts. The proposed strategy has been experimentally evaluated, and the results confirm that it was capable of dealing with fragile and flexible objects. In addition, the influence of the loop time of the digital controller on force control for this task was also investigated in mathematical and simulated ways. Furthermore, a series of experiments were designed to explore the effects that have influences on errors in force control. The main factors that affect force control error were analyzed.

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Pouring from Deformable Containers Based on Tactile Information Using a Dual-Arm Robot

International Journal of Robotic Computing ◽

10.35708/rc1868-126254 ◽

2019 ◽

Vol 1 (2) ◽

pp. 123-143

Author(s):

Yuto Tsuchiya

Keyword(s):

Success Rate ◽

Motion Capture ◽

The Other ◽

Motion Capture System ◽

Breakfast Cereal ◽

Tactile Information ◽

Coffee Beans ◽

Arm Motion ◽

Dual Arm Robot ◽

Dual Arm

In this paper, we consider household robots that pour various contents from deformable containers. Such pouring is often seen in cooking and refilling. To achieve this kind of pouring, we reduce the deformation of the container during pouring and thus carefully design the grasping strategy: the palm of one hand supports the deformable container from the bottom and the other hand pulls up the container from the top. We apply the proposed system to pouring four different kinds of contents: breakfast cereal, coffee beans, flour, and rice. The experiment verifies that the proposed system successfully pours the four contents. To evaluate the system quantitatively, we measure 1) the deformation of the container using a motion capture system and 2) the success rate of pouring. We verify that the dual-arm pouring reduced the deformation by 66% compared to a single-arm motion and that the success rate is greater than 90%.

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