Abstract
Over the last two decades, the foundations for physical human–robot interaction (GlossaryTerm
pHRI
) 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.
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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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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