Bioinspired robotics is a fascinating field that's pushing the boundaries of what machines can do. Imagine robots that can walk, fly, swim, and climb like animals do. These so-called multimodal robots are rapidly advancing, and they're not just about adding more movement options; they're about improving overall performance in challenging environments. This article explores the exciting world of bioinspired multimodal robots, the engineering challenges they face, and a new framework for evaluating their performance.
The Evolution of Bioinspired Multimodal Robots
Bioinspired multimodal robots are machines that can switch between multiple forms of movement, such as walking, flying, swimming, climbing, or jumping. These robots are rapidly advancing, and they're not just about adding more movement options; they're about improving overall performance in challenging environments. The field has evolved from combining separate mechanisms to creating integrated, animal-inspired systems that use shared structures and intelligent control for greater adaptability and efficiency.
The main goal of multimodal robotics is not merely to add more movement options but to improve overall performance in challenging environments. A robot that can both fly and walk, for example, can use flight for rapid long-distance travel before switching to walking for precise inspection on the ground. Similarly, amphibious robots can transition between land and water to perform search-and-rescue operations, environmental monitoring, or underwater exploration.
Engineering Challenges
The study identifies several major engineering challenges that must be overcome to make these robots practical. One of the biggest obstacles is limited onboard space, as every additional movement mode requires actuators, sensors, batteries, and mechanical components that increase size and weight. Components useful in one mode can become dead weight in another, reducing efficiency.
Another challenge is body morphing—the ability to physically reconfigure the robot’s structure to support different types of movement. Designers must also balance stiffness and flexibility, integrate different actuation systems, and ensure that multiple locomotion modes work together rather than interfere with one another.
Performance Evaluation
To address the lack of standardized evaluation methods, the researchers propose five performance metrics for multimodal robots. These measure the number of movement modes a robot possesses, the additional cost of adding new capabilities, how many components can be shared across different modes, the time or energy required to switch between modes, and the overall performance gains achieved by combining multiple forms of locomotion.
Emerging Design Strategies
The review also examines emerging design strategies that could improve future robots. Soft materials and flexible structures allow robots to deform and adapt to their surroundings, while structure repurposing enables the same components to perform multiple functions. Another promising approach is multirobot architecture, in which teams of simple robots cooperate to achieve multimodal capabilities collectively.
Software and AI Advancements
On the software side, the researchers note that conventional planning and control algorithms struggle with the dramatic changes in dynamics that occur when robots switch movement modes. They argue that advances in reinforcement learning, vision-language-action models, world models, and physically intelligent robot bodies will be essential for enabling seamless transitions and autonomous decision-making in complex environments.
The Future of Multimodal Robots
Looking ahead, the authors envision multimodal robots that tightly integrate adaptive hardware with AI-driven perception, planning, and control. Achieving this will require advances in materials, high-performance actuators, sensors, and learning algorithms capable of handling unpredictable real-world conditions. If these challenges can be overcome, the researchers argue, future bioinspired multimodal robots could not only match the versatility of animals but, in some applications, surpass their natural counterparts.
In conclusion, bioinspired multimodal robots are a rapidly evolving field with immense potential. By addressing the engineering challenges and advancing the underlying technologies, we may soon see robots that can truly mimic the agility and adaptability of nature.
