The scope of the IEEE RAS TC Model-based optimization for robotics is the development and application of model-based optimization techniques for the generation and control of dynamic behaviors in robotics and their practical implementation.
Rigid Body Dynamics Algorithms by Roy Feathearstone A comprehensive collection of the best rigid-body dynamics algorithms.
A Mathematical Introduction to Robotic Manipulation by Richard M. Murray, Zexiang Li S. Shankar Sastry A good mathematical introduction to various robotics concepts (includes Lie groups and screw theoretic description)
Geometric Fundamentals of Robotics by Jon Selig Geometric foundations of Robotics (demonstrates links to Lie Algebra, Study Quadric, Clifford Algebra etc.)
Convex optimization, Stephen Boyd and Lieven Vandenberghe An excellent introduction of the theory and concepts of optimization as well as some important classes of algorithm with numerous practical exemples from various fields.
Numerical optimization, Jorge Nocedal and Stephen J. Wright A comprehensive and up-to-date description of the most effective methods in continuous optimization, striking a good balance between theory and pratical implementation considerations. A must have for those wanting to implement their own solvers.
Optimization Algorithms on Matrix Manifolds, P.-A. Absil, R. Mahony, and R. Sepulchre A more advance and mathematically involved book, tackling the problem of optimization on non-Euclidean manifolds, which is getting some attention in robotics.
Applied optimization
Nonlinear Programming: Concepts, Algorithms, and Applications to Chemical Processes, Lorenz T. Biegler This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.
Practical Methods for Optimal Control and Estimation Using Nonlinear Programming, Second Edition, John T. Betts The book describes how sparse optimization methods can be combined with discretization techniques for differential-algebraic equations and used to solve optimal control and estimation problems. The interaction between optimization and integration is emphasized throughout the book.
