With Autonomous Mobile Robots (AMRs), the usual risks arc those of collision between a worker and the AMR, or a body part trapped between the AMR and a fixed or moving obstacle. To bypass obstacles (human or otherwise), AMRs feature autonomous control systems activating safety-related functions based on machine learning or optimization algorithms. This paper proposes a roadmap to guide integrators and users on the safe implementation of two AMRs. To do so, a risk assessment of two identical AMRs was performed, using ISO 12100, in a test bed consisting of an Intelligent Cyber-Physical Systems laboratory warehouse at Polytechnique Montreal. A safety checklist from the standard R15.08 was filled out to feed the risk assessment process and to help judge the efficiency of the technical protective measures, namely the safety-related functions. Apart from the risks of collision and entrapment, the risk assessment highlighted other hazards stemming from the AMRs, such as intense light that can temporarily distort someone's view, then potentially become a pitfail during human-robot interactions. Assessing the autonomous localization and mapping ability of the AMRs at their configuration phase highlighted the importance of a high quality and reliable Wi-Fi to detect obstacles on time and avoid unexpected movements. Consequently, the risks have started being addressed to use those AMRs safely. The study showed the gap between today's safety-related state of the art (e.g., R15.08, ISO/IEC TR 5469) and the manufacturer's design choices. That gap will raise awareness amongst designers, so they prioritize more inherently safe principles.
Zhang et al. (Tue,) studied this question.