Passive noninteracting control for human-robot team interaction

Abstract

This paper is motivated by the control of robot teams by a human. Control challenges arise because i) typically, the team needs to achieve multiple control objectives, shared between the robot team and the human, in order to accomplish a task, ii) robust stability needs to be guaranteed to facilitate the safe interaction with the human and the apriori unknown environment. The concept of passivity has been successfully applied for robust stabilization of robotic systems, however, not in the context of shared control in human-robot team interaction. In this paper we propose a novel control approach which decouples the robot team dynamics into multiple subsystems, each having a different control objective. The proposed control law, suitable for the interaction of the robot team with the human or environment, guarantees passivity of the subsystems. The approach is illustrated in a simulation.

How and When Can Robots Be Team Members? Three Decades of Research on Human–Robot Teams

“…Findings indicate that somewhat autonomous robots and shared control can facilitate the work of human team members and make HRTs more efficient (e.g., Lee et al, 2010;Lewis et al, 2010;Sellner et al, 2006). Researchers also have proposed an algorithm to predict team performance, based on the robot's performance in interaction with human team members or when it is autonomous (Crandall et al, 2003), as well as various control approaches for human-directed robot teams (Musić et al, 2019;Musić & In most of the studies, the robot morphology, robot level, and type of embodiment are not specified. The six studies that provide information (Abrams & der Pütten, 2020;Dudenhoeffer et al, 2001;Gladden, 2014;Manikonda et al, 2007;Talamadupula et al, 2014;Yazdani et al, 2016) focus on functional robots (e.g., Growbot [Dudenhoeffer et al, 2001], Pioneer P3-AT [Talamadupula et al, 2014]) and indicate different robot levels (lower/same and higher level) and embodiments (physical robot; simulation).…”

“…The six studies that provide information (Abrams & der Pütten, 2020; Dudenhoeffer et al, 2001; Gladden, 2014; Manikonda et al, 2007; Talamadupula et al, 2014; Yazdani et al, 2016) focus on functional robots (e.g., Growbot [Dudenhoeffer et al, 2001], Pioneer P3-AT [Talamadupula et al, 2014]) and indicate different robot levels (lower/same and higher level) and embodiments (physical robot; simulation). d In most of the studies, the team setup is not specified. The two studies that provide information focus on human-directed robot teams (Musić & Hirche, 2018; Yazdani et al, 2016). …”

“… d In most of the studies, the team setup is not specified. The two studies that provide information focus on human-directed robot teams (Musić & Hirche, 2018; Yazdani et al, 2016). …”

Human–Robot Team Interaction Through Wearable Haptics for Cooperative Manipulation

“…In this subsection we define robot team subtasks and briefly propose control strategy suitable for cooperative manipulation. For a more detailed explanation of the control approach used the reader is referred to [2] and [33].…”

“…We use the subtask Jacobians as projection matrices to obtain maps of the robot team dynamics in lower dimensional spaces [33]. Let us now formulate relative and cooperative constraints for cooperative manipulation task conducted by two robots as depicted in Fig.…”