Current Trends in Legged and Multimodal Robotics

Recent advancements in the field of legged and multimodal robotics have seen a significant shift towards more robust and adaptive control frameworks. Innovations in state estimation for legged robots have focused on addressing the challenges posed by foot slippage and leg deformation, leading to the development of dual estimation frameworks that enhance robustness through adaptive filtering techniques. These methods not only improve the accuracy of state estimation but also contribute to better control and stability in dynamic environments.

In the realm of multimodal robots, there is a growing emphasis on optimization-free control strategies that leverage momentum observers to estimate external forces and ground reaction forces. These approaches aim to simplify control algorithms, making them more efficient and less reliant on heavy computational resources. The integration of thrusters with legged systems has opened new possibilities for complex maneuvers, such as steep slope walking, which were previously unattainable.

The use of bio-inspired morphing wing flight techniques has also seen advancements, with researchers developing more accurate force estimation methods that enhance the stability and control of flapping-wing systems. These developments are crucial for the future of autonomous aerial navigation and robust flight control.

Noteworthy papers include one that introduces a dual beta-Kalman filter for robust state estimation in legged robots, significantly outperforming state-of-the-art methods. Another notable contribution is the optimization-free control framework for multimodal legged-aerial robots, which demonstrates the potential for more efficient and adaptable control strategies.