The multifaceted human sense of touch is fundamental to direct manipulation, but technical challenges prevent most teleoperation systems from providing even a single modality of haptic feedback, such as force feedback. This paper postulates that ungrounded grip-force, fingertip-contact-and-pressure, and high-frequency acceleration haptic feedback will improve human performance of a teleoperated pick-and-place task. Thirty subjects used a teleoperation system consisting of a haptic device worn on the subject's right hand, a remote PR2 humanoid robot, and a Vicon motion capture system to move an object to a target location. Each subject completed the pick-and-place task 10 times under each of the eight haptic conditions obtained by turning on and off grip-force feedback, contact feedback, and acceleration feedback. To understand how object stiffness affects the utility of the feedback, half of the subjects completed the task with a flexible plastic cup, and the others used a rigid plastic block. The results indicate that the addition of grip-force feedback with gain switching enables subjects to hold both the flexible and rigid objects more stably, and it also allowed subjects who manipulated the rigid block to hold the object more delicately and to better control the motion of the remote robot's hand. Contact feedback improved the ability of subjects who manipulated the flexible cup to move the robot's arm in space, but it deteriorated this ability for subjects who manipulated the rigid block. Contact feedback also caused subjects to hold the flexible cup less stably, but the rigid block more securely. Finally, adding acceleration feedback slightly improved the subject's performance when setting the object down, as originally hypothesized; interestingly, it also allowed subjects to feel vibrations produced by the robot's motion, causing them to be more careful when completing the task. This study supports the utility of grip-force and high-frequency acceleration feedback in teleoperation systems and motivates further improvements to fingertip-contact-and-pressure feedback.
A teleoperation system with high transparency enables the operator to focus on completing the task at hand instead of on controlling the robot. We previously proposed that modifying the mapping from human movement to desired robot movement might improve the transparency of teleoperators in ways similar to adding sensory feedback. Specifically, we created non-Cartesian motion mappings that correct for systematic reaching errors made by humans, so that the robot motion resembles the operator's intent rather than his or her produced movement. This article presents a study that compares subjects' performance on a virtual teleoperated targeting task under three different motion mappings: a Cartesian-scaling motion mapping that is typically implemented in teleoperators, a corrective variable-similarity motion mapping that is fit to aggregate data from subjects in a previous study, and a corrective variable-similarity motion mapping that is fit to calibration data collected from each subject. Twelve participants reached toward 120 targets under each of the three motion mappings with balanced random presentation order and a washout task between conditions. Subjects were able to complete the targeting task with higher accuracy in the initial direction of robot motion, at higher speeds, and with more natural and efficient reaching movements under the variable-similarity motion mappings. Subjects also overwhelmingly preferred the variable-similarity motion mappings. These results indicate that subjects experienced a higher level of transparency when using the virtual teleoperator with the variable-similarity motion mappings than with the standard Cartesian mapping. Therefore, mappings that correct for systematic errors in human motion, such as the variable-similarity motion mappings tested here, should be considered in teleoperator design.
This paper presents a novel approach to haptic teleoperation. Specifically, we use control barrier functions (CBFs) to generate force feedback to help human operators safely fly quadrotor UAVs. CBFs take a control signal as input and output a control signal that is as close as possible to the initial control signal, while also meeting specified safety constraints. In the proposed method, we generate haptic force feedback based on the difference between a command issued by the human operator and the safe command returned by a CBF. In this way, if the user issues an unsafe control command, the haptic feedback will help guide the user towards the safe input command that is closest to their current command. We conducted a within-subject user study, in which 12 participants flew a simulated UAV in a virtual hallway environment. Participants completed the task with our proposed CBFbased haptic feedback, no haptic feedback, and haptic feedback generated via parametric risk fields, which is a state-of-the-art method described in the literature. The results of this study show that CBF-based haptic feedback can improve a human operator's ability to safely fly a UAV and reduce the operator's perceived workload, without sacrificing task efficiency.
OpenBU http://open.bu.edu Mechanical Engineering BU Open Access Articles 2019-07 Effects of force-torque and tactile haptic modalities on classifying the success of robot manipulat...
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