Human Like Adaptation of Force and Impedance in Stable and Unstable Tasks

Abstract—This paper presents a novel human-like learning con-troller to interact with unknown environments. Strictly derived from the minimization of instability, motion error, and effort, the controller compensates for the disturbance in the environment in interaction tasks by adapting feedforward force and impedance. In contrast with conventional learning controllers, the new controller can deal with unstable situations that are typical of tool use and gradually acquire a desired stability margin. Simulations show that this controller is a good model of human motor adaptation. Robotic implementations further demonstrate its capabilities to optimally adapt interaction with dynamic environments and humans in joint torque controlled robots and variable impedance actuators, with-out requiring interaction force sensing. Index Terms—Feedforward force, human motor control, impedance, robotic control. I

Robot companions for citizens

This paper describes the scientific vision and objectives of the FET Flagship candidate initiative Robot Companions for Citizens. Robot Companions will be a new generation of machines that will primarily help and assist elderly people in activities of daily living in their workplace, home and in society. They will be the ICT solution for a new sustainable welfare

Collision detection and safe reaction with the DLR-III lightweight manipulator arm

A robot manipulator sharing its workspace with humans should be able to quickly detect collisions and safely react for limiting injuries due to physical contacts. In the absence of external sensing, relative motions between robot and human are not predictable and unexpected collisions may occur at any location along the robot arm. Based on physical quantities such as total energy and generalized momentum of the robot manipulator, we present an efficient collision detection method that uses only proprioceptive robot sensors and provides also directional information for a safe robot reaction after collision. The approach is first developed for rigid robot arms and then extended to the case of robots with elastic joints, proposing different reaction strategies. Experimental results on collisions with the DLR-III lightweight manipulator are reported

Best Application Paper Award IROS 2008

Best Application Paper Award 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, F, September 200

Collision detection and reaction: A contribution to safe physical human-robot interaction

In the framework of physical Human-Robot Interaction (pHRI), methodologies and experimental tests are presented for the problem of detecting and reacting to collisions between a robot manipulator and a human being. Using a lightweight robot that was especially designed for interactive and cooperative tasks, we show how reactive control strategies can significantly contribute to ensuring safety to the human during physical interaction. Several collision tests were carried out, illustrating the feasibility and effectiveness of the proposed approach. While a subjective "safety" feeling is experienced by users when being able to naturally stop the robot in autonomous motion, a quantitative analysis of different reaction strategies was lacking. In order to compare these strategies on an objective basis, a mechanical verification platform has been built. The proposed collision detection and reactions methods prove to work very reliably and are effective in reducing contact forces far below any level which is dangerous to humans. Evaluations of impacts between robot and human arm or chest up to a maximum robot velocity of 2.7 m/s are presented. ©2008 IEEE

Friction observer and compensation for control of robots with joint torque measurement

In this paper we introduce a friction observer for robots with joint torque sensing (in particular for the DLR medical robot) in order to increase the positioning accuracy and the performance of torque control. The observer output corresponds to the low-pass filtered friction torque. It is used for friction compensation in conjunction with a MIMO controller designed for flexible joint arms. A passivity analysis is done for this friction compensation, allowing a Lyapunov based convergence analysis in the context of the nonlinear robot dynamics. For the complete controlled system, global asymptotic stability can be shown. Experimental results validate the practical efficiency of the approach. ©2008 IEEE

A dataset of continuous affect annotations and physiological signals for emotion analysis

From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research, direct, real-time inspection in realistic settings is not possible. Discrete, indirect, post-hoc recordings are therefore the norm. As a result, proper emotion assessment remains a problematic issue. The Continuously Annotated Signals of Emotion (CASE) dataset provides a solution as it focusses on real-time continuous annotation of emotions, as experienced by the participants, while watching various videos. For this purpose, a novel, intuitive joystick-based annotation interface was developed, that allowed for simultaneous reporting of valence and arousal, that are instead often annotated independently. In parallel, eight high quality, synchronized physiological recordings (1000 Hz, 16-bit ADC) were made of ECG, BVP, EMG (3x), GSR (or EDA), respiration and skin temperature. The dataset consists of the physiological and annotation data from 30 participants, 15 male and 15 female, who watched several validated video-stimuli. The validity of the emotion induction, as exemplified by the annotation and physiological data, is also presented

Biomechanisch sichere Geschwindigkeitsregelung fur die Mensch-Roboter Interaktion

Roboter zu bef¨ahigen sicher mit dem Menschen zu interagieren ist eine essentielle Zielstellung der Roboterforschung. In diesem Sinne ist sicheres Roboterverhalten sogar unter Worst-Case Situationen essentiell und bildet auch die Basis f¨ur kognitive Entscheidungsprozesse. In diesem Artikel n¨ahern wir uns dem Problem aus verletzungsmedizinischer Sicht, um eine Relation zwischen Kollisionsmasse, -geschwindigkeit und -geometrie, sowie der damit verbundenen Verletzung im medizinischen Sinne abzuleiten. Diese Einsichten werden derart repr¨asentiert, dass ein biomechanisch sicherer Geschwindigkeitsregler abgeleitet werden kann, der dieses zuvor erzeugte Wissen nutzt. Der Algorithmus wertet in Echtzeit die reflektierte Tr¨agheit, Geschwindigkeit und Oberfl¨achengeometrie an m¨oglichen Kollisionspunkten entlang der Roboterstruktur aus. Enabling robots to safely interact with humans is an essential goal of robotics research. In these terms, safe behavior of the robot even under worst-case situations is crucial and forms also a basis for higher level decisional aspects. In this paper we approach the problem from a medical injury analysis point of view in order to formulate the relation between robot mass, velocity, impact geometry, and resulting injury qualified in medical terms. We transform these insights into processable representations and propose a motion controller that utilizes injury knowledge for generating safe robot motions. The algorithm takes into account the reflected inertia, velocity, and geometry at possible impact locations