Validation of a tuning method for haptic shared control using neuromuscular system analysis

This research investigates a neuromuscular analysis based tuning procedure for haptic shared control systems that has been hypothesized to improve subjective operator workload when compared to heuristic tuning methods. Here, the tuning procedure takes into consideration the response of the neuromuscular system to haptic cues. Human arm stiffness, the neuromuscular property of concern, can be changed by modulating reflex strength. The `relax task´ setting of the neuromuscular system, for which reflexes are minimized, is chosen as the design point for tuning haptic cues as it is hypothesized to lead to the lowest workload. A simulated haptic collision avoidance system for unmanned aircraft teleoperation is used as a platform to experimentally validate the tuning method. The results show that the novel tuning procedure, particularly for relax task tuning, substantially improves workload and situational awareness over conditions that ignores the neuromuscular system. Additionally, over-tuning, which frequently occurs for heuristic methods, leads to worse user acceptance than a condition without haptic support.