The recent advancements in robotics and control systems have shown a strong emphasis on improving the efficiency, accuracy, and robustness of various robotic platforms and control methodologies. A notable trend is the integration of geometric optimization and novel control strategies to address the limitations of traditional methods. For instance, distributed inverse dynamics control for quadruped robots has been advanced through the use of geometric optimization, enabling more stable and efficient locomotion. Similarly, backstepping control has been applied to tendon-driven continuum robots, offering smoother trajectories and better performance in the presence of external disturbances. In the realm of mechatronics, higher-order sinusoidal input describing functions have been introduced to enhance the performance of reset control systems, providing a more precise and efficient control mechanism. Additionally, the modeling of complex robotic systems, such as parallel kinematic manipulators with hybrid limbs, has been streamlined using constraint embedding techniques, facilitating more accurate and systematic dynamic modeling. Furthermore, uncertainty-aware model predictive control has been developed for motorized LiDAR systems, significantly improving odometry accuracy while maintaining efficiency. Lastly, energy-efficient SLAM approaches have been proposed by jointly optimizing sensing, communication, and exploration speed, contributing to the development of lifelong SLAM systems. High-accuracy model predictive control with inverse hysteresis has also been demonstrated for high-speed trajectory tracking of piezoelectric fast steering mirrors, offering superior tracking performance and robustness.

Noteworthy papers include one on distributed inverse dynamics control for quadruped robots, which significantly reduces foot slippage and improves orientation tracking, and another on backstepping control for tendon-driven continuum robots, demonstrating smoother trajectories and reduced settling time.