Abstract
The success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment. The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Regarding the former, to properly manage interaction dynamics on the robot control side, an estimation of the human behaviors and intentions is necessary. In this letter, we present the building blocks of such a human-in-the-loop controller, and validate them in both simulation and on the iCub humanoid robot using a human–robot interaction scenario. In this scenario, a human assists the robot in standing up from being seated on a bench.
Highlights
T HE ability to interact with and manipulate the environment gives robots a distinct advantage over purely software based automated agents
In this work, we model both the robot and the human with the same mathematical formalism. This choice is motivated by the fact that we would like to use the estimated human state and dynamics as additional feedback in robot controllers when physical human-robot interaction (pHRI) scenarios are considered
Once f ∗, the optimal value for f is determined, the second stage consists in computing the joint torque required to reach the desired value for the contact force-torques at the feet. This computation is achieved by solving a constrained quadratic program (QP), with f ∗ and torques τ related by equations (1a),(1c)
Summary
T HE ability to interact with and manipulate the environment gives robots a distinct advantage over purely software based automated agents. In the FP7 European project, CoDyCo, the focus was on how to properly exploit contact dynamics in the control of the robot. Foreseen robotic applications range from the use of robots as service and elderly assistants, to their use in industrial plants in close contact with. Manuscript received: May, 24, 2017; Revised September, 20, 2017; Accepted October, 11, 2017. This paper was recommended for publication by Editor Allison M. Okamura upon evaluation of the Associate Editor and Reviewers’ comments.
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