<p>This book presents a unified mathematical treatment of diverse problems in the</p><p>general domain of robotics and associated fields using Clifford or geometric alge-</p><p>bra. By addressing a wide spectrum of problems in a common language, it offers</p><p>both fresh insights and new solutions that are useful to scientists and engineers</p><p>working in areas related with robotics.</p><p> </p><p>It introduces non-specialists to Clifford and geometric algebra, and provides ex-</p><p>amples to help readers learn how to compute using geometric entities and geomet-</p><p>ric formulations. It also includes an in-depth study of applications of Lie group</p>theory, Lie algebra, spinors and versors and the algebra of incidence using the<p></p><p>universal geometric algebra generated by reciprocal null cones.</p><p>Featuring a detailed study of kinematics, differential kinematics and dynamics</p><p>using geometric algebra, the book also develops Euler Lagrange and Hamiltoni-</p><p>ans equations for dynamics using conformal geometric algebra, and the recursive</p><p>Newton-Euler using screw theory in the motor algebra framework. Further, it</p><p>comprehensively explores robot modeling and nonlinear controllers, and discusses</p><p>several applications in computer vision, graphics, neurocomputing, quantum com-</p><p>puting, robotics and control engineering using the geometric algebra framework.</p><p>The book also includes over 200 exercises and tips for the development of future</p><p>computer software packages for extensive calculations in geometric algebra, and a</p><p>entire section focusing on how to write the subroutines in C++, Matlab and Maple</p><p>to carry out efficient geometric computations in the geometric algebra framework.</p><p>Lastly, it shows how program code can be optimized for real-time computations.</p><p>An essential resource for applied physicists, computer scientists, AI researchers,</p><p>roboticists and mechanical and electrical engineers, the book clarifies and demon-</p><p>strates the importance of geometric computing for building autonomous systems</p>to advance cognitive systems research.<p></p><br><p></p>
