A new method for achieving smooth gait transitions in hexapod robots

Robots that can move quickly and efficiently across different terrains could be of great advantage as they could successfully carry out complex missions in challenging environments. For example, these robots could help monitor complex natural environments such as forests or search for survivors after natural disasters.

One of the most commonly used types of robots designed to navigate across diverse terrain are legged robots, whose body designs are often inspired by the body structure of animals. To move quickly across diverse terrain, legged robots must be able to adapt their movements and gaits to detected changes in their environmental conditions.

Researchers at the Higher Institute for Applied Science and Technology in Damascus, Syria, recently developed a new method to enable a smooth transition between the different gaits of a hexapod robot.

Their proposed gait control technique, presented in an article published in Heliyonis based on so-called central pattern generators (CPGs), computational approaches that mimic biological CPGs, the neural networks that underlie many rhythmic movements of humans and animals (e.g. walking, swimming, jogging, etc.).

“Our recent publication is a fundamental part of a larger project that aims to revolutionize the locomotion control of hexapod robots,” Kifah Helal, corresponding author of the paper, told Tech Xplore.

“Even though machine learning techniques have not yet been integrated, the architecture we have developed lays the foundation for such advanced applications. Our methodology is designed for the future integration of machine learning and ensures that once implemented, it will significantly improve disturbance compensation.”

Helal and his colleagues first started by designing and simulating a six-legged (hexapod) robot. This simulated robot platform was then used to test their proposed control architecture based on CPGs.

“Our control method leverages the principles of CPGs, where each leg of the hexapod robot is controlled by a specific rhythmic signal,” explained Helal. “The essence of the different gaits lies in the phase differences between these signals. The main contribution of our paper is the novel interaction design between the oscillators, which ensures seamless gait transitions.”

Helal and his colleagues also developed a workspace trajectory generator, a computational tool that translates the outputs of the oscillators built into a hexapod robot into trajectories for its feet, ensuring that these trajectories remain effective during transitions. Initial tests showed that their proposed control architecture enables stable, efficient, and fast gait changes in both a simulated and real hexapod robot.

“The most striking results of our research are the harmonious blend of smooth transitions and speed,” said Helal. “Essentially, it is the fusion of fluidity and speed that sets our work apart from other previous efforts. We also validated a mapping function that ensures that the robot’s foot trajectory remains effective during these transitions.”

The research team’s new architecture could soon be tested in further experiments and applied to other walking robots to enable them to quickly adapt to environmental changes while maintaining their agility.

In their next studies, Helal and his colleagues plan to further improve their method, fix potential malfunctions and further improve their performance when robots encounter particularly challenging terrain.

“In the future, we want to focus more on machine learning to further refine our robot’s ability to adapt to the environment,” added Helal. “We are particularly excited about researching malfunction compensation and integrating pain sensors as feedback mechanisms.”

“These advances will not only improve the robot’s interaction with its environment, but will also pave the way for more autonomous and resilient robotic systems.”

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