RCA: Ride Comfort-Aware Visual Navigation via Self-Supervised Learning

Understand

Under shared autonomy, wheelchair users expect vehicles to provide safe and comfortable rides while following users high-level navigation plans.

• To find such a path, vehicles negotiate with different terrains and assess their traversal difficulty.
• Most prior works model surroundings either through geometric representations or semantic classifications, which do not reflect perceived motion intensity and ride comfort in downstream navigation tasks.
• We propose to model ride comfort explicitly in traversability analysis using proprioceptive sensing.