Impact of Active vs. Passive Robot Behavior on Task Efficiency in Collaborative Physical HRI
Alessandro Tiozzo, Giulia Scorza Azzarà , Alessandro Rizzo, Alessandra Sciutti, Francesco Rea
AI summary
Problem
Non-adaptive, passive robot behaviors disrupt coordination and reduce task efficiency when human partners change pace. The paper addresses how to design control strategies that enable robots to dynamically adapt to human timing without relying on computationally expensive force feedback.
Approach
The researchers developed an adaptive impedance controller for the iCub humanoid robot that dynamically adjusts stiffness, damping, and movement velocity based on real-time kinematic feedback. This allows the robot to mimic human motion timing and modulate its compliance during a collaborative sawing task using a flexible wire.
Key results
- Increased robot contribution via adaptive velocity and mimicry
- Higher synchronization and task performance compared to passive control
- Greater energy consumption required to maintain active synchronization
- Successful dynamic phase transitions without direct force feedback
Why it matters
Highlights the critical trade-off between behavioral adaptivity and energy cost in physical HRI, guiding engineers and researchers in designing efficient, responsive collaborative robots for real-world applications.
Abstract
Advancements in physical Human-Robot Interac- tion (pHRI) aim to achieve natural and efficient collaboration between humans and robots, especially in dynamic environments where task performance is essential. This study focuses on co- manipulative human-robot joint activities, exploring key compo- nents of performance and synchronization. The primary objective was to design an active control technique for the iCub robot’s arms that enhances task efficiency with a distinct approach than traditional force feedback controls. Comparing an iCub’s passive behavior with the designed active one has registered an increase in its contribution, given through adaptive velocity and mimicry, and showcasing its ability to respond dynamically to changes in human actions. Furthermore, a measurement of the exertion applied by the counterparts revealed that the active behavior required greater energy consumption to reach those levels of synchronization and performance. These results highlight the implications of balancing active behavior with effort intensity to achieve task efficiency in pHRIs.