Paper Info
Title
Evaluation Of A Novel Biologically Inspired Trajectory Generator In Human-Robot Interaction
Abstract
In many future joint-action scenarios, humans and robots will have to interact physically in order to cooperate successfully. Ideally, human-robot interaction should not require training on the human side, but should be intuitive and simple. Previously, we reported on a simple case of physical human-robot interaction, a hand-over task [I]. Even such a basic task as manually handing over an object from one agent to another requires that both partners agree upon certain basic prerequisites and boundary conditions. While some of them are negotiated explicitly, e.g. by verbal communication, others are determined indirectly and adaptively in the course of the cooperation. In the previous study we compared a human-human hand-over interaction with the same task performed by a human and a robot. However, the trajectories used for the robot, a conventional trapezoidal velocity profile in joint coordinates and a minimum-jerk profile of the end-effector, have little resemblance to the natural movements of humans. In this study we introduce a novel trajectory generator that is a variation of the traditional minimum-jerk profile, the 'decoupled minimum-jerk' profile. Its trajectory is much closer to those observed in human-human experiments. We evaluated its performance concerning human comfort and acceptance in a simple hand-over experiment by using a past-test questionnaire. The evaluation of the questionnaire revealed no difference with respect to comfort, human-likeness, or subjective safety of the new planner compared to the minimum-jerk profile. Thus, the 'decoupled minimum-jerk' planner, which offers important advantages with respect to target approach, proved to be a promising alternative to the previously used minimum-jerk profile.
Year
DOI
Venue
2009
10.1109/ROMAN.2009.5326233
RO-MAN 2009: THE 18TH IEEE INTERNATIONAL SYMPOSIUM ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, VOLS 1 AND 2
Keywords
Field
DocType
end effector,robot kinematics,human robot interaction,end effectors,path planning,boundary condition,trajectory
Motion planning,Computer vision,Simulation,Computer science,Planner,Robot kinematics,Robot end effector,Artificial intelligence,Robot,Grippers,Trajectory,Human–robot interaction
Conference
Citations 
PageRank 
References 
6
1.26
3
Authors
7
Name
Order
Citations
PageRank
Markus Huber161.26
Helmuth Radrich261.26
Cornelia Wendt3162.43
Markus Rickert421722.78
Alois Knoll Knoll51700271.32
Thomas Brandt614416.15
Stefan Glasauer7899.46