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Robot Planning with Mathematical Models of Human State and Action
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Robots interacting with the physical world plan with models of physics. We advocate that robots interacting with people need to plan with models of cognition. This writeup summarizes the insights we have gained in integrating computational cognitive models of people into robotics planning and control. It starts from a general game-theoretic formulation of interaction, and analyzes how different approximations result in different useful coordination behaviors for the robot during its interaction with people.
Forward citations
Cited by 2 Pith papers
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HumanFlow -- Diffusion-Driven MAV Navigation Among Humans via Tightly-Coupled Motion Tracking, Forecasting, and Control
HumanFlow is a latent diffusion model for unified human motion tracking and forecasting in 3D scenes, tightly coupled via flow-matching MPC to an approximate policy for MAV social navigation that outperforms prior met...
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HumanHalo -- Safe and Efficient 3D Navigation Among Humans via Minimally Conservative MPC
The paper contributes a linear MPC safety constraint that, for the first control input alone, prevents the drone's future reachable set from ever being fully inside a human's reachable set, avoiding inevitable collisions.
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