Leafbot soft robot shows potential for disaster relief

Leafbot has been developed by a team at the Japan Advanced Institute of Science and Technology (JAIST). Led by Professor Van Anh Ho and involving doctoral students Linh Viet Nguyen and Khoi Thanh Nguyen, the researchers explored Leafbot’s adaptability across various uneven surfaces and terrains. Their findings have been published in the IEEE Transactions on Robotics.

“Soft robots are increasingly recognised for their ability to navigate complex and unstructured environments, making them valuable for applications such as inspection and exploration. By leveraging a vibration-driven motion, we have designed a robot capable of overcoming such complex obstacles with minimal control mechanisms,” Prof. Ho said in a statement.

According to JAIST, conventional vibration-based robots often require complex control algorithms to handle irregular terrains. In contrast, Leafbot uses its compliant structure of soft materials with a simple yet effective locomotion strategy to traverse slopes and navigate obstacles.

The team designed the Leafbot's structure using a soft monolithic silicone rubber with curved projections at the base to replicate limbs for crawling. The body of the soft robot was then attached to a vibrating motor to enable a vibration mechanism for locomotion.

To explain the physics behind Leafbot’s movement, the research team developed an analytical model incorporating factors such as centripetal forces, asymmetric friction interactions, and limb deformation. Using finite element analysis simulations, they further refined their understanding of how the soft structure interacts with different terrains.

“We aimed to analyse how morphology influences locomotion. The experimental results validated our predictions, depicting how specific limb patterns optimise Leafbot’s performance across challenging landscapes,” said Prof. Ho.

The researchers also conducted extensive empirical testing. Three robot models with different limb configurations were compared for performance across various terrains, including slopes, semi-circular barriers, and step-field terrains.

They found that the robot’s curved limb morphology played a critical role in overcoming obstacles, enabling it to traverse slopes of up to 30 degrees as well as semi-circular barriers. Additionally, the successful integration of theoretical modelling and experimental validation ensured that Leafbot’s design was effective and scalable.

“Unlike rigid robots, which rely on precise actuation, Leafbot’s adaptability allows for self-adjustment across different surfaces. This ability makes it particularly useful for applications that require mobility in confined and uneven spaces,” said co-author Linh Viet Nguyen.

According to the team, Leafbot could undertake missions in disaster-stricken areas, where fallen debris and uneven ground pose challenges. They could also be used for inspecting pipelines, underground explorations, and other industrial settings that require autonomous mobility. Furthermore, these dynamic robots can also find applications in agriculture for activities like soil analysis and crop inspection, enabling precision farming.
Co-author Khoi Thanh Nguyen, said: “We believe that insights from our research, combined with advancements in AI and machine learning, could eventually enable tasks to be performed with minimal human intervention.”

“By integrating sensory feedback systems and improving its energy efficiency, we envision Leafbot evolving into an autonomous system capable of real-time terrain adaptation and decision-making, transforming the field of soft robotics.”