Books

Robot Modeling and Control

• Modern Robotics - Mechanics, Planning and Control by Kevin M. Lynch and Frank C. Park
  A good introduction to many concepts of model-based robotics.
• 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.)
  
• Robot and Multibody Dynamics: Analysis and Algorithms by Abhinandan Jain
  Comprehensive textbook on multibody dynamics algorithms using Spatial Operator Algebra (SOA)

Numerical computations and optimizations

• 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.