The role of roles: Physical cooperation between humans and robots

Abstract

Since strict separation of working spaces of humans and robots experiences a softening due to recent robotics research achievements, close interaction of humans and robots comes rapidly into reach. In this context, physical human-robot interaction raises a number of questions regarding a desired intuitive robot behavior. The continuous bilateral information and energy exchange requires an appropriate continuous robot feedback. Investigating a cooperative manipulation task, the desired behavior is a combination of an urge to fulfill the task, a smooth instant reactive behavior to human force inputs and an assignment of the task effort to the cooperating agents. In this paper, a formal analysis of human-robot cooperative load transport is presented. Three different possibilities for the assignment of task effort are proposed. Two proposed dynamic role exchange mechanisms adjust the robot's urge to complete the task based on the human feedback. For comparison, a static role allocation strategy not relying on the human agreement feedback is proposed as well. All three role allocation mechanisms are evaluated in a user study that involves large-scale kinesthetic interaction and full-body human motion. Results show tradeoffs between subjective and objective performance measures stating a clear objective advantage of the proposed dynamic role allocation scheme.

Digital Transformation of Engineering Education - Empirical Insights from Virtual Worlds and Human-Robot-Collaboration

“…But due to reasons of efficiency and productivity of the whole team the test subjects started to switch these roles during the experiment. This is also a well-known fact within this research field as several studies have revealed that a continuous dynamic role allocation is superior over a constant role strategy [17]. Regarding to the results of the described experiment this flexibility of role allocation is also a characteristic of humanrobot-teams.…”

Adaptive optimal control for coordination in physical human-robot interaction

“…Interpreting the role adaptation law (14), the robot adjusts its role according to the new role of the human. Specifically, whenever the human interacts with the robot by exerting a force f , the weight R 2 will be updated via (14), until f tracks the optimal control f * .…”

“…Risk-sensitive optimal feedback control is proposed in [11], which is the basis of the following two works: in [12], role adaptation is achieved by adaptive attitude design depending on both the disagreement level and environmental situation; and in [13], an adaptation strategy is developed to switch between model-based and model-free predictions in the case of partially known tasks. In [14], a shared plan of human and the robot is given as a desired trajectory of the object configuration and the common goal of the cooperation is known to both agents. In [15], impedance parameters of the human arm are estimated online, and the leader/follower role of robot is switched according to the recognized human intention.…”

Rapid Prototyping of Planning, Learning and Control in Physical Human-Robot Interaction

“…The quality of assistance benefits from goal-oriented robot behavior -in contrast to purely reactive behavior -as shown for example in a cooperative load transport task [17,22]. For simplicity and clarity we focus here on the physical assistance in the redundant degrees of freedom of the task, i.e.…”

“…Potential methods for decision and blending are proposed in this work. The interaction control layer can be implemented as static role allocation (leader/follower) [17] or dynamic effort sharing strategy [22]. Alternatively, a risk-sensitive optimal feedback control scheme can be applied to generate an intuitive robot force contribution depending on observed human execution variability [21].…”