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Physical Human–Robot Interaction

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Abstract

Over the last two decades, the foundations for physical human–robot interaction (GlossaryTermpHRI) have evolved from successful developments in mechatronics, control, and planning, leading toward safer lightweight robot designs and interaction control schemes that advance beyond the current capacities of existing high-payload and high-precision position-controlled industrial robots. Based on their ability to sense physical interaction, render compliant behavior along the robot structure, plan motions that respect human preferences, and generate interaction plans for collaboration and coaction with humans, these novel robots have opened up novel and unforeseen application domains, and have advanced the field of human safety in robotics.

This chapter gives an overview on the state of the art in pHRI. First, the advances in human safety are outlined, addressing topics in human injury analysis in robotics and safety standards for pHRI. Then, the foundations of human-friendly robot design, including the development of lightweight and intrinsically flexible force/torque-controlled machines together with the required perception abilities for interaction are introduced. Subsequently, motion-planning techniques for human environments, including the domains of biomechanically safe, risk-metric-based, human-aware planning are covered. Finally, the rather recent problem of interaction planning is summarized, including the issues of collaborative action planning, the definition of the interaction planning problem, and an introduction to robot reflexes and reactive control architecture for pHRI.

Keywords

  • Contact Force
  • Collision Detection
  • Joint Torque
  • Industrial Robot
  • Impedance Control

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The original version of this chapter was revised. The erratum to this chapter is available at DOI https://dx.doi.org/10.1007/978-3-319-32552-1_81

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Fig. 69.1
Fig. 69.2a–f
Fig. 69.3
Fig. 69.4
Fig. 69.5a–e
Fig. 69.6
Fig. 69.7a,b
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Fig. 69.14a–c
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Fig. 69.30

Abbreviations

3-D:

three-dimensional

AO:

Arbeitsgemeinschaft für Ostheosynthesefragen

CC:

compression criterion

CHMM:

continuous hidden Markov model

COMAN:

compliant humanoid platform

DARPA:

Defense Advanced Research Projects Agency

DC:

dynamic constrained

DHMM:

discrete hidden Markov model

DLR:

Deutsches Zentrum für Luft- und Raumfahrt

DNF:

dynamic neural field

DOF:

degree of freedom

DPC:

dynamic partially constrained

DU:

dynamic unconstrained

fs:

force sensor

HASY:

hand arm system

HIC:

head injury criterion

HIII:

Hybrid III dummy

HMM:

hidden Markov model

IIT:

Istituto Italiano di Tecnologia

IM:

injury measure

ISO:

International Organization for Standardization

LWR:

light-weight robot

MRI:

magnetic resonance imaging

NASA:

National Aeronautics and Space Agency

PCA:

principal component analysis

pHRI:

physical human–robot interaction

PI:

possible injury

POI:

point of interest

QSC:

quasistatic constrained

RGB-D:

red–green–blue–depth

SEA:

series elastic actuator

SME:

small and medium enterprises

SMU:

safe motion unit

TORO:

torque controlled humanoid robot

TS:

technical specification

UBC:

University of British Columbia

VAS:

visual analog scale

VIA:

variable impedance actuator

VSA:

variable stiffness actuator

WCF:

worst-case factor

WCR:

worst-case range

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Haddadin, S., Croft, E. (2016). Physical Human–Robot Interaction. In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-32552-1_69

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