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If you only want a single comprehensive text on Robotics, I would recommend the Springer Handbook of Robotics. I covers everything from controls and artificial intelligence to perception and mechanics …

I agree with holmeski's suggestion that an accelerometer is the way to go for static projects, but if you need more sophisticated measurements, an accelerometer/gyroscope combo will be necessary. The …

The answer to this is simple, but the other answers obfuscate the dynamics. Differential drive robots can be modeled with unicycle dynamics of the form: $$\left[\begin{matrix}\dot{x}\\ \dot{y} \\ \do …

If I understand correctly, you would like to understand how control a two-wheeled differential drive robot so that you can achieve smooth/elegant driving while arriving at a desired final orientation- …

Chow's Theorem states that: The driftless system $$\dot q=g_1(q)u_1+...+g_m(q)u_m$$ is locally controllable at $q_0\in\mathbb{R}^n$ if $\text{rank}\bar\Delta(q_0)=n.$ Here, $\bar\Delta$ is the i …

The short answer to this question is that linearization won't work, and here's why: Differential drive robots can be modeled with unicycle dynamics of the form: $$\dot{z}=\left[\begin{matrix}\dot{x}\ …

The theory that describes what you are looking for is call Control Theory. Search for the Nonlinear Systems textbook by Hassan Khalil for an excellent overview of the material--the inverted pendulum p …

In the probabilistic approaches that you mentioned, specifically Monte Carlo Localization (MCL), the prediction step is made based on state (pose) information and measurements. MCL relies on the Marko …

The problem is that you can't apply path planning until you know where the robot is in the global coordinate frame. There are many localization techniques, and each has its pros/cons; I have used Part …