In order to move quickly across different terrains, legged robots must be able to adapt their movements and walking style based on detected body changes.Researchers at the Higher Institute of Applied Science and Technology in Damascus, Syria, recently developed a new method to facilitate smooth transitions between different gaits in a six-legged robot. The proposed gait control technology was introduced in the document published by Heliyon. These are the basic neuronal networks of many rhythm movements by humans and animals (that is, walking, swimming, jogging, etc.).

"Our recent publication is a larger project component aimed at completely change the control of the sixth -type robot movement. "Although machine learning technology has not yet been integrated, the architecture we have developed is the foundation for such advanced applications. Our approach was designed with the future integration of machine learning in mind, ensuring that when implemented, it will significantly improve error compensation."Helal and his colleagues first began to design and model the hexapods. This simulated robot platform was then used to test their proposed CPG-based control architecture.

"Our control method uses CPG principles, where each leg of the hexapod is controlled by a different rhythm signal," explains Helal. "The essence of different gaits lies in the phase difference between these signals. The main contribution of our paper is the new design of the interaction between the oscillators, which provides seamless gait transitions.

Hellar and his colleagues also developed a workspace trajectory generator, a computational tool that transforms the output of the hexapod's integrated oscillators into the trajectories of its feet, ensuring that those trajectories remain valid. Preliminary tests demonstrated that their proposed control architecture is capable of achieving stable, efficient, and fast gait changes in simulated and real hexapod robots. "The most striking result of our research is the harmonious combination of smoothness and speed of the transition," says Heral. "Fundamentally, the fusion of fluidity and speed sets our work apart from others that have come before it. We also check the mapping function that ensures that the robot's foot pin is still effective during these transitions.