At a High-Level

• Markov Chain Monte Carlo (MCMC) algorithms to sample diverse, nearly-optimal trajectories for motion planning
• Experiments on a 2D navigation and 3D manipulation problems
• Second-derivative information helpful for sampling in 3D manipulation problems
• MCMC motion planners may help robots better model humans and improve human-robot collaboration

Motivation

To model an agent, we can define a probabilistic model

Motivation

To model an agent, we can define a probabilistic model

A popular model of the behavior of an agent with goals is that of Boltzmann rationality.

Motivation

To model an agent, we can define a probabilistic model

A popular model of the behavior of an agent with goals is that of Boltzmann rationality.

It models a kind of approximately rational behavior.

Stochastic Optimization in Motion Planning

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