Expectable Motion Unit: Avoiding Hazards From Human Involuntary Motions in Human-Robot Interaction

TL;DR

This work addresses safety in human-robot interaction by considering both physical injury risks and human expectations that can trigger involuntary motions. It introduces the Expectable Motion Unit (EMU), a cognitive-grounded safety module that, based on a risk matrix linking robot speed and distance to the probability of involuntary motion (IMO), derives an expectation curve to limit robot velocity in real time; EMU is cascaded with the Safe Motion Unit (SMU) to ensure both perceptual and biomechanical safety. The approach is grounded in a 29-participant experimental study that maps $v_r$ and $d_h$ to IMO frequency, yielding a practical implementation that produces $v_{EMU}$ and a final safe velocity $v_{safe} = \min\{v_d, v_{SMU}, v_{EMU}\}$ for $d_h \le d_{max}$. Validation shows EMU reduces IM in five of six tested approaches, with near-contact cases still challenging, underscoring the potential to improve safety, acceptance, and trust in HRI by aligning robot behavior with human expectations while respecting biomechanical limits.

Abstract

In robotics, many control and planning schemes have been developed to ensure human physical safety in human-robot interaction. The human psychological state and the expectation towards the robot, however, are typically neglected. Even if the robot behaviour is regarded as biomechanically safe, humans may still react with a rapid involuntary motion (IM) caused by a startle or surprise. Such sudden, uncontrolled motions can jeopardize safety and should be prevented by any means. In this letter, we propose the Expectable Motion Unit (EMU), which ensures that a certain probability of IM occurrence is not exceeded in a typical HRI setting. Based on a model of IM occurrence generated through an experiment with 29 participants, we establish the mapping between robot velocity, robot-human distance, and the relative frequency of IM occurrence. This mapping is processed towards a real-time capable robot motion generator that limits the robot velocity during task execution if necessary. The EMU is combined in a holistic safety framework that integrates both the physical and psychological safety knowledge. A validation experiment showed that the EMU successfully avoids human IM in five out of six cases.

Figures (7)

• Figure 1: Proposed framework for safe human-aware motion generation that combines cognitive-grounded safety aspects and well-established physical safety considerations and paradigms. The main contribution of this work is an experimental model of human involuntary motion (IM) occurrence in HRI and the derivation of the Expectable Motion Unit (EMU), which avoids potentially dangerous human IM in HRI.
• Figure 2: Derivation of the EMU. The first step is to experimentally investigate under which circumstances human IMO occur (b). Using the experimental resultsprobability (between 1 and 0) of IMO resulting the experiment , an IMO risk matrix is assembled (c). The risk matrix allows us to define expectation curves, that can be embedded into the EMU (d), which is finally combined with the SMU to ensure both physical and perceived safety.
• Figure 3: Experimental setup and procedure: (a) The participant focuses on a quiz while the robot moves at some distance. (b) The robot approaches towards distance $d_h$. (c) The camera captures mimics and gestures.
• Figure 4: Exploratory velocity-distance risk matrix for IMO with two exemplary expectation curves for the IM thresholds $q_r = 0.15$ and $q_r = 0.30$. Depending on the human-robot distance, the expectation curves provide a robot velocity that avoids IM with the selected probability $q_r$.
• Figure 5: Total number of S-S cues for all participants over the number of an robot approaching motions.