Dataset Information

Human-Inspired Robotic Eye-Hand Coordination Enables New Communication Channels Between Humans and Robots.

ABSTRACT: This paper concerns human-inspired robotic eye-hand coordination algorithms using custom built robotic eyes that were interfaced with a Baxter robot. Eye movement was programmed anthropomorphically based on previously reported research on human eye-hand coordination during grasped object transportation. Robotic eye tests were first performed on a component level where accurate position and temporal control were achieved. Next, 11 human subjects were recruited to observe the novel robotic system to quantify the ability of robotic eye-hand coordination algorithms to convey two kinds of information to people during object transportation tasks: first, the transported object's delivery location and second, the level of care exerted by the robot to transport the object. Most subjects correlated decreased frequency in gaze fixations on an object's target location with increased care of transporting an object, although these results were somewhat mixed among the 11 human subjects. Additionally, the human subjects were able to reliably infer the delivery location of the transported object purely by the robotic eye-hand coordination algorithm with an overall success rate of 91.4%. These results suggest that anthropomorphic eye-hand coordination of robotic entities could be useful in pedagogical or industrial settings.

SUBMITTER: Olson S

PROVIDER: S-EPMC8513751 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Human-Inspired Robotic Eye-Hand Coordination Enables New Communication Channels Between Humans and Robots.

Olson Stephanie S Abd Moaed M Engeberg Erik D ED

International journal of social robotics 20200918 5

This paper concerns human-inspired robotic eye-hand coordination algorithms using custom built robotic eyes that were interfaced with a Baxter robot. Eye movement was programmed anthropomorphically based on previously reported research on human eye-hand coordination during grasped object transportation. Robotic eye tests were first performed on a component level where accurate position and temporal control were achieved. Next, 11 human subjects were recruited to observe the novel robotic system ...[more]

PMID: 34659586

Similar Datasets

Project description:Backgroundfor many technology-driven visuomotor tasks such as tele-surgery, human operators face situations in which the frames of reference for vision and action are misaligned and need to be compensated in order to perform the tasks with the necessary precision. The cognitive mechanisms for the selection of appropriate frames of reference are still not fully understood. This study investigated the effect of changing visual and kinesthetic frames of reference during wrist pointing, simulating activities typical for tele-operations.Methodsusing a robotic manipulandum, subjects had to perform center-out pointing movements to visual targets presented on a computer screen, by coordinating wrist flexion/extension with abduction/adduction. We compared movements in which the frames of reference were aligned (unperturbed condition) with movements performed under different combinations of visual/kinesthetic dynamic perturbations. The visual frame of reference was centered to the computer screen, while the kinesthetic frame was centered around the wrist joint. Both frames changed their orientation dynamically (angular velocity = 36 degrees /s) with respect to the head-centered frame of reference (the eyes). Perturbations were either unimodal (visual or kinesthetic), or bimodal (visual+kinesthetic). As expected, pointing performance was best in the unperturbed condition. The spatial pointing error dramatically worsened during both unimodal and most bimodal conditions. However, in the bimodal condition, in which both disturbances were in phase, adaptation was very fast and kinematic performance indicators approached the values of the unperturbed condition.Conclusionsthis result suggests that subjects learned to exploit an "affordance" made available by the invariant phase relation between the visual and kinesthetic frames. It seems that after detecting such invariance, subjects used the kinesthetic input as an informative signal rather than a disturbance, in order to compensate the visual rotation without going through the lengthy process of building an internal adaptation model. Practical implications are discussed as regards the design of advanced, high-performance man-machine interfaces.

Project description:Hand-eye calibration is an important step in controlling a vision-guided robot in applications like part assembly, bin picking and inspection operations etc. Many methods for estimating hand-eye transformations have been proposed in literature with varying degrees of complexity and accuracy. However, the success of a vision-guided application is highly impacted by the accuracy the hand-eye calibration of the vision system with the robot. The level of this accuracy depends on several factors such as rotation and translation noise, rotation and translation motion range that must be considered during calibration. Previous studies and benchmarking of the proposed algorithms have largely been focused on the combined effect of rotation and translation noise. This study provides insight on the impact of rotation and translation noise acting in isolation on the hand-eye calibration accuracy. This deviates from the most common method of assessing hand-eye calibration accuracy based on pose noise (combined rotation and translation noise). We also evaluated the impact of the robot motion range used during the hand-eye calibration operation which is rarely considered. We provide quantitative evaluation of our study using six commonly used algorithms from an implementation perspective. We comparatively analyse the performance of these algorithms through simulation case studies and experimental validation using the Universal Robot’s UR5e physical robots. Our results show that these different algorithms perform differently when the noise conditions vary rather than following a general trend. For example, the simultaneous methods are more resistant to rotation noise, whereas the separate methods are better at dealing with translation noise. Additionally, while increasing the robot rotation motion span during calibration enhances the accuracy of the separate methods, it has a negative effect on the simultaneous methods. Conversely, increasing the translation motion range improves the accuracy of simultaneous methods but degrades the accuracy of the separate methods. These findings suggest that those conditions should be considered when benchmarking algorithms or performing a calibration process for enhanced accuracy.

Dataset Information

Human-Inspired Robotic Eye-Hand Coordination Enables New Communication Channels Between Humans and Robots.

Publications

Human-Inspired Robotic Eye-Hand Coordination Enables New Communication Channels Between Humans and Robots.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets