Human–Robot Interaction¶

Status: emerging
Last updated: 2026-05-31
Sources: 9781119636113.Ch44.Pdf
Tags: [human-robot-interaction, autonomy, situation-awareness, trust-in-automation, teleoperation, multi-robot-control, workload]

Summary¶

Human-robot interaction (HRI) concerns how people work with robots across a spectrum that has evolved from using tools, to controlling platforms, to supervising automated systems, to collaborating with autonomous agents (Chen & Barnes, 2021). The chapter surveys HRI applications from single-robot teleoperation to multiple robots and swarms, and analyses human-factors issues including situation awareness, trust, workload, and psychomotor aspects. A central concern is calibrated trust, supported by agent transparency about system purpose, process, and performance.

Body¶

Context¶

Chen and Barnes (2021), in their handbook chapter on human-robot interaction (HRI), examine how people work with robots across a spectrum that has evolved from using tools, to controlling platforms, to supervising automated systems, to collaborating with autonomous agents. They survey applications from single-robot teleoperation to multiple robots and swarms, and analyse human-factors issues including situation awareness, trust, workload, and psychomotor aspects. Within this knowledge base the article sits on the autonomy strand alongside Supervisory Control Of Automation and Automation Autonomy And Ai, shares its calibrated-trust and transparency concern with Human Centered Design Of Ai, and draws its core human-factors constructs from Situation Awareness and Mental Workload.

Key Points¶

The human-robot relationship has evolved toward collaboration — from using robots as tools, to controlling platforms, to supervising automated systems, to collaborating with autonomous agents, whether embodied robots or disembodied algorithms. Chen and Barnes cite the US National Science Foundation's National Robotics Initiative as a large effort promoting human collaboration with co-robots, framing HRI as moving beyond direct control toward partnership with increasingly autonomous systems (PDF p. 1, orig. p. 1121).

The chapter spans a range of applications and autonomy levels: single-robot manual control and teleoperation, semiautonomous and autonomous single robots, and multiple robots and swarms. HRI design must therefore address both the close-coupled control of a teleoperated robot and the supervisory demands of overseeing many semi-autonomous agents at once (PDF pp. 2–6, orig. pp. 1122–1126).

Situation awareness, workload, and psychomotor factors are key human-factors issues alongside trust. Supervising multiple autonomous systems raises workload and situation-awareness challenges that connect HRI directly to supervisory control and mental workload (PDF p. 12, orig. p. 1132).

Calibrated trust and transparency are central. Increasing autonomy creates new issues such as mutual trust, and systems should support calibrated trust to reduce misuse and disuse by being transparent about system purpose, process, and performance — the 3Ps (Chen et al., 2018; Lee & See, cited in Chen & Barnes, 2021) (PDF p. 8, orig. p. 1128).

Conclusion¶

Chen and Barnes (2021) conclude that as robots become more autonomous, the central HRI challenge is calibrated trust — trust matched to a system's actual reliability. They treat agent transparency about purpose, process, and performance as the design mechanism for achieving it, linking HRI to the broader work on human-automation trust, situation awareness, and workload.

References¶

Chen, J.Y.C. & Barnes, M.J. (2021) 'Human–Robot Interaction', in Salvendy, G. & Karwowski, W. (eds.) Handbook of Human Factors and Ergonomics. 5th edn. Hoboken, NJ: John Wiley & Sons. chen2021humanrobot

Open Questions¶

How does agent transparency need to scale when one human supervises many autonomous robots?
What design factors most strongly determine whether operator trust in a robot is well calibrated to its actual reliability?