Probabilistic Robotics

This text serves as a standard reference for the probabilistic approach to robotics, a field that treats uncertainty as a central problem rather than an edge case. The authors, prominent figures in the field, provide a rigorous yet accessible introduction to the mathematical frameworks used to enable robots to perceive, plan, and control their movements in dynamic, noisy environments.

The book systematically covers key topics such as state estimation, localization, mapping, and path planning, emphasizing the use of Bayesian inference and stochastic processes. It is written in a clear, academic register suitable for advanced undergraduates and graduate students, bridging the gap between theoretical probability and practical robotic implementation.

Description adapted from Open Library bibliographic data ↗.