Kinematic Model

Kinematic models mathematically describe the motion of systems, focusing on geometry and position without considering forces. Current research emphasizes developing accurate and computationally efficient kinematic models for diverse applications, including robotics (e.g., manipulators, mobile robots, and continuum robots), human motion analysis, and autonomous vehicle safety. Researchers are exploring various model architectures, such as Gaussian mixture models and neural networks, often combined with advanced algorithms like Kalman filtering and reinforcement learning to improve model accuracy and robustness in challenging scenarios. These advancements have significant implications for improving the control, safety, and performance of robots and other dynamic systems.