Shared-Control HMI for Tactile-First Traversal Offline Counterfactual Evaluation with Haptic Safety Projection

Abstract

Supervising tactile-first robotic traversal in confined, uncertain spaces poses a challenge: operators must be able to intervene without continuous micromanagement. We present a human-machine interface (HMI) that blends operator commands with safety-constrained autonomy and surfaces risk through synthesized predictive haptic alerts. Using offline, log-driven replay of 660 trials, we counterfactually evaluate this HMI without new user studies. Results show consistent improvements: predicted collisions decrease, minimum clearance increases, traversal time and path length improve, and the traversability certificate margin rises. Operator-autonomy disagreement is reduced, with smoother control and fewer heading reversals, particularly under algorithms M2 and M3. Importantly, the synthesized haptic alerts anticipate safety-critical events with positive lead time, achieving high precision and recall as objective measures of informativeness. Together, these findings indicate that shared-control blending with tactile-first autonomy can enhance safety, efficiency, and assurance while reducing conflict between operator intent and autonomy. Contributions include the method (counterfactual shared control with safety projection), metrics for safety/efficiency/assurance/conflict, empirical results across 660 trials, and release of replay and haptic-synthesis artifacts. This positions tactile-first HMI as a practical pathway for safe, low-overhead operator supervision in vision-denied, contact-rich environments.