We just wanted a category to put the excellent Probabilistic Robotics in, so read its review for more information.
Sebastian Thrun, Wolfram Burgard, Dieter Fox
- In-text exercises
- Errata, videos, etc.
Who wouldn't be excited about an applied probability book involving robots?! This is an exceptionally well-produced text that purports to about robotics, but it is actually quite useful to anyone who uses applied probability (ex. data scientists). Its explanations of various kinds of filtering, such as the Kalman filter and particle filtering, are extremely lucid; frankly, this book does a better job with filtering than other books that are dedicated to the subject. Obviously this book contains a lot of material that is specific to robotics, such as a litany of simultaneous location and mapping (SLAM) algorithms. Thrun et al. should be very accessible to those at the undergraduate level, and it is a fun read for all.