Human-centric Path Planning and Motion Behaviour Analysis in Hazardous Environments

Abstract

Hazardous work environments, such as nuclear facilities and construction sites, present critical safety challenges that need more attention. While nuclear operations expose workers to imperceptible radiation risks, construction activities involve physically demanding tasks that contribute to ergonomic injuries such as musculoskeletal disorders (MSDs). Persistent risks in hazardous environments require more effective solutions to address their unique occupational challenges through advanced technologies. This research explores the potential of augmented reality (AR) and virtual reality (VR) for improving safety through human-centric design, focusing on path planning in radiation environments and human motion analysis in masonry as potential use cases. The research addresses the practicality issues during their implementation and assesses the feasibility of the developed solutions. The first study develops an AR-based path planning system in radiation environments. Here, path planning algorithms in existing methods only prioritize exposure minimization but result in routes poorly suited for human navigation, such as zigzagged paths with too many turns or paths that are unnecessarily long just to follow the lowest doses. To overcome this, I propose a two-stage human centric path planning framework. First, the A*-based algorithm is enhanced with a novel multi objective cost function to generate candidate paths that balance cumulative radiation exposure, travel distance, and the number of turns. Second, a parameter sweep procedure is introduced to select Pareto-optimal solutions. Unlike traditional methods that prioritize either radiation reduction or path length, this framework offers users a variety of path options tailored to their specific needs. Also, considering fewer turns for easier navigation, this approach is more intuitive than traditional robot centric path planning methods, offering greater flexibility and safety for workers in real-world applications. The second study evaluates VR’s efficacy for training in masonry work to reduce ergonomic risks like MSDs while lifting heavy blocks. While VR training is effective in training for various fields, its effectiveness in teaching proper ergonomic posture and reducing injury risks has not been thoroughly explored. This study conducted experiments to compare real lifts (lifting physical blocks in a real world setting) and VR lifts (lifting virtual weightless blocks in a VR-simulated environment), assessing motion behaviour in both contexts. In both experiments, while performing the same tasks of lifting blocks, participants were asked to wear a motion capture suit to record the motion data. The collected data were processed for analysis using the Rapid Upper Limb Assessment (a standard test for ergonomic risk), followed by a detailed analysis of the scores for body sections, including upper arm, lower arm, neck, and trunk. Experimental results demonstrate a significant statistical difference in motion behaviour between VR and real-life tasks, particularly in the trunk and neck. We conclude that VR training developments for the trades must recognize this limitation.