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.
Mazurick et al. (Tue,) studied this question.