Advancing Human-Robot Collaboration through SimulationPURPOSE OF THE STUDYInfotiv, as part of the research project ArtWork (The Smart and Connected Worker), is continuing its investigation into simulation and digital twins for human-robot collaborative manufacturing environments. Building directly on the foundational work carried out in RITA-SIM[1] and SIMLAN[2] simulation platforms, this thesis aims to advance the platform from a proof-of-concept demonstrator towards a robust human-robot collaboration system.The current RITA-SIM implementation relies on ground-truth simulator data for collision avoidance and task execution, and its pick-and-place scenarios are limited in scope and resilience. This thesis addresses those gaps by introducing real perception, predictive human-awareness, richer humanoid simulation, and scenarios. The goal is to evaluate and improve the effectiveness of simulation for one or several of the items below:Replacing ground-truth collision data with a camera-based perception pipeline for robust, sensor-realistic obstacle avoidancePredicting human movement trajectories in the shared workspace so the robot can plan proactively rather than reactively.Implementing end-to-end kitting task sequences (advance scenarios) that handle continuous operation, part variation, and real-world failure modes such as misaligned partsExpanding humanoid simulation scenarios and investigating live interactive control of a virtual human agent inside SimulatorImproving multi-camera localisation and agent tracking accuracy, and evaluating machine learning models for human pose estimation and activity recognition in the factory floor simulationThe study will produce open-source contributions to the RITA-SIM and SIMLAN repository and validate findings both in simulation an…MjukvarutestareSystemtestare och testledare
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