Dataset Information

Synchronization-based control for a collaborative robot.

ABSTRACT: This article introduces a new control scheme for controlling a robotic manipulator in a collaborative task, allowing it to respond proactively to its partner's movements. Unlike conventional robotic systems, humans can operate in an unstructured, dynamic environment due to their ability to anticipate changes before they occur and react accordingly. Recreating this artificially by using a forward model would lead to the huge computational task of simulating a world full of complex nonlinear dynamics and autonomous human agents. In this study, a controller based on anticipating synchronization, where a 'leader' dynamical system is predicted by a coupled 'follower' with delayed self-feedback, is used to modify a robot's dynamical behaviour to follow that of a series of leaky integrators and harmonic oscillators. This allows the robot (follower) to be coupled with a collaborative partner (leader) to anticipate its movements, without a complete model of its behaviour. This is tested by tasking a simulated Baxter robot with performing a collaborative manual coordination task with an autonomous partner under a range of feedback delay conditions, confirming its ability to anticipate using oscillators instead of a detailed forward model.

SUBMITTER: Eberle H

PROVIDER: S-EPMC7813249 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Synchronization-based control for a collaborative robot.

Eberle Henry H Nasuto Slawomir J SJ Hayashi Yoshikatsu Y

Royal Society open science 20201216 12

This article introduces a new control scheme for controlling a robotic manipulator in a collaborative task, allowing it to respond proactively to its partner's movements. Unlike conventional robotic systems, humans can operate in an unstructured, dynamic environment due to their ability to anticipate changes before they occur and react accordingly. Recreating this artificially by using a forward model would lead to the huge computational task of simulating a world full of complex nonlinear dynam ...[more]

PMID: 33489276

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Project description:This article provides a perspective on estimation and control problems in cyberphysical human systems (CPHSs) that work at the intersection of cyberphysical systems and human systems. The article also discusses solutions to some of the problems in CPHSs. One example of a CPHS is a close-proximity human-robot collaboration (HRC) in a manufacturing setting. The issue of the joint operation's efficiency and human factors, such as safety, attention, mental states, and comfort, naturally arise in the HRC context. By considering human factors, robots' actions can be controlled to achieve objectives, including safe operations and human comfort. Alternately, questions arise when robot factors are considered. For example, can we provide direct inputs and information to humans about an environment and the robots in the area such that the objectives of safety, efficiency, and comfort can be satisfied by considering the robots' current capabilities? The article discusses specific problems involved in HRC related to controlling a robot's motion by taking the current actions of the human in the loop with the robot's control system. To this end, two main challenges are discussed: 1) inferring the intention behind human actions by analyzing a person's motion as observed through skeletal tracking and gaze data and 2) a controller design that keeps robot motion constrained to a boundary in a 3D space by using control barrier functions. The intention inference method fuses skeleton-joint tracking data obtained using the Microsoft Kinect sensor and human gaze data gathered from red-green-blue Kinect images. The direction of a human's hand-reaching motion and a goal-reaching point is estimated while performing a joint pick-and-place task. The trajectory of the hand is estimated forward in time based on the gaze and hand motion data at the current time instance. A barrier function method is applied to generate safe robot trajectories along with forecast hand movements to complete the collaborative displacement of an object by a person and a robot. An adaptive controller is then used to track the reference trajectories using the Baxter robot, which is tested in a Gazebo simulation environment.

Project description:To elucidate the working mechanism behind anthropomorphism, this study investigated whether human participants would anthropomorphize a robot more if they move synchronously versus non-synchronously with it, and whether this is affected by which of the two initiates the movements. We tested two competing hypotheses. The feature-overlap hypothesis predicts that moving in synchrony would increase perceived self-other feature overlap, which in turn might spread activation to codes of features related to humans-which should increase anthropomorphization. In contrast, the autonomy hypothesis predicts that unpredictability increases anthropomorphization, and thus that whenever the robot initiates movements, or when the human initiates movements to which the robot moves non-synchronously, there is an increased perception of the robot as a more human-like, intentionally acting creature, which in turn should increase anthropomorphization. We performed a study with synchrony as within-subjects factor, and initiator (robot or human) as between-subjects factor. To study the impact of synchrony on self-other overlap and perception of human likeness, participants completed two tasks that served as implicit measures of state anthropomorphization, and two questionnaires that served as explicit measures of state anthropomorphization toward the robot. The two implicit measures were the joint Simon task and one-shot Dictator Game. Additionally, participants filled in a trait anthropomorphization questionnaire, to enable correction for baseline tendencies to anthropomorphize. The synchrony manipulation did not affect the joint Simon effect, although there was an effect on average reaction time (RT), where in the group in which the robot initiated the movement, RTs were slower when the human and robot moved non-synchronously. The Dictator Game offer and the state anthropomorphization questionnaires were not affected by the synchrony manipulation. There was, however, a positive correlation between current anthropomorphization of the robot and amount of money offered to it. Given that most measures were not systematically affected by our manipulation, it appears that either our design was suboptimal, or that synchronization does not affect the anthropomorphization of a robot.

Dataset Information

Synchronization-based control for a collaborative robot.

Publications

Synchronization-based control for a collaborative robot.

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