Foundations of Robot Motion Planning and Control

Motion is at the heart of robotics, but programming a robot to move smoothly and avoid obstacles requires a solid grasp of mathematical planning and control. This text-based course guides you through the fundamental algorithms and control strategies that power modern robotic systems. By reading through our structured explanations and working through practical written exercises, you will develop a clear understanding of how robots calculate trajectories, plan collision-free paths, and execute precise physical movements. What you'll learn: - Understand the fundamental mathematics behind robot kinematics, configuration spaces, and motion planning. - Learn how to generate smooth trajectories and transition profiles for robotic joints. - Apply obstacle avoidance techniques and path-planning algorithms, including sampling-based and grid search methods. - Configure basic feedback control systems, including PID controllers, to ensure precise execution of planned paths. - Explore modern concepts in motion control, including state-space representation and basic obstacle avoidance models. The course begins with core definitions of configuration spaces and obstacle representations, then progresses to trajectory generation, path-planning algorithms, and feedback control loops. This course is designed for beginners, aspiring robotics engineers, and students who want to understand the theoretical and algorithmic foundations of robotic movement without requiring prior advanced robotics experience. Start reading today to master the core principles of robotic motion planning and control.