← Back to Benchmarks
simmediumpolicy-learningmetric · varies
NavThinker: Action-Conditioned World Models for Coupled Prediction and Planning in Social Navigation
Description
Social navigation requires robots to act safely in dynamic human environments. Effective behavior demands thinking ahead: reasoning about how the scene and pedestrians evolve under different robot actions rather than reacting to current observations alone. This creates a coupled prediction-planning challenge, where robot actions and human motion mutually influence each other. To address this challenge, we propose NavThinker, a future-aware framework that couples an action-conditioned world model