Human-Robot Interaction Lecture 7 – Dynamical System Modeling

French school/university system and expectations / relationships between students Know the methods for dynamic modeling of flexible robotic manipulators.

1SC2410 – Studying and modeling electromagnetic conversion systems and Lecture #6: Introduction to dynamic programming. Lecture #7: Ford-Bellman ...

10 mai 2021 kinect vision system combined with robot's model and ... collision with dynamic obstacles (humans or objects) [7] [8]

Know how to model the dynamical behavior of a manufacturing robot organs of a robot or a robotic system in interaction with the humans for design

deal with Robotics systems as a whole rather than just to concentrate on one dynamic modelling and its applications classical PID controller and ...

21 févr. 2020 It is only with the unveiling of the Honda P2 humanoid robot in ... behavior of this dynamical system to answer questions like

9 févr. 2016 method on HAZOP and to combine it with the system modeling language ... the human-robot interactions

19 oct. 2016 Using a rule-based framework our system is able to model and maintain humans' mental beliefs allowing the robot to understand what humans.

Dynamic Systems" - 7° ed. Ed. Pearson Publishing Company

13 oct. 2015 Nonverbal Combined Behavior in Human–Robot Interaction. Autonomous Robots ... dialogue systems that are adapted to the user's model.

Human-robot interaction · Human-robot teaming · Joint action · Dynamicalgroup modeling · Coordination 1 Introduction As robots are becoming more ubiquitous they will be expected to interact withpeople in a range of settings from dyads to groups

goal in sight: A successful human-robot interaction in terms of safety performance and human satisfaction Efforts toward model completeness and accuracy should be focused on those aspects of human behavior to which interaction success is most sensitive We emphasise that identifying which those aspects are

generated by the dynamical system and the real trajectory in?uenced by the human interaction) We provide analytical analysis and several simulations of our method Finally we investigate our approach through real world experiments with a 7-DOF KUKA LWR 4+ robot performing tasks such as polishing and pick-and-place I INTRODUCTION

THE HUMAN AGENT SYSTEM The Human Agent System is a model for human- robot interaction based on interpersonal interactions There are several components of the Human Agent System which are depicted in Fig 2 The Human Agent gets input from Human Input Agents and operates on a Human Database

Aug 12 2020 · Human-Robot Interaction (HRI) is a relatively new branch of robotics research and application It involves the understanding design and evaluation of robotics systems that will interact with humans [1] It has been an established multidisciplinary research field since the early 2000s

Figure 2:a) b)Model of the human-exoskeleton system: a)c) the human biomechanics b) the exoskeleton model c) the cooperative human-exoskeleton system 3 1 Musculoskeletal model of the human upper body The musculoskeletal model of the human upper body is modeled as a multi-body system where human bones

to understand model and address complex aspects of evaluation of human-robot interaction 1 INTRODUCTION HRI (Human-Robot Interaction) has several impor-tant similarities with HCI (Human-Computer Inter-action) Models of interaction created for HCI have been applied and modi?ed for HRI (Scholtz 2003)

Modeling Dynamical In?uence in Human Interaction Wei Pan 1 Wen Dong Manuel Cebrian;2 Taemie Kim1 James H Fowler2 Alex (Sandy) Pentland1 1Media Laboratory MIT 20 Ames Street Cambridge MA 01239 USA 2University of California San Diego 9500 Gilman Drive La Jolla CA 92093 USA

Chapter 2 Robot control 2 1General robot control In this chapter we present our mathematical formulation for the control of robot (using DS-based impedance control) motion generation (using parameterized dynamical systems) and motion adaptation (using proposed gradient-based methods)

3 Experiments on Human Interaction Data We here demonstrate an application of using our dynamical in?uence process to predict turn taking– who will speak next in the interaction process and we show that it is possible to achieve good accuracy in prediction given only the binary audio volume variance observations with no informa-

We conduct a user study with the JACO2 7-DoF robotic arm to assess how online learning from physical interactions during a task affects the robot’s objective performance as well as subjective participant perceptions Overall our work is a ?rst step towards learning robot objectives online from pHRI 2Related Work

One approach proposed for an ef?cient human-robot col-laboration is to predict the human movement during the experiment and optimize the path for the robot to avoid colliding with the human [16] [17] Although this may work for some scenarios it does not solve the core problem of HRI the mutual understanding of each one’s action For