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Self-Reconfigurable Robots and Digital Hormones
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Self-reconfigurable robots can change shape to navigate diverse environments, but their complex control software, dubbed 'digital hormones,' is still under development.
Key Insights
Self-reconfigurable robots are designed to autonomously change their physical configurations, such as shapes and sizes, to adapt to different missions and environments.
The 'Superbot' project, initially sponsored by NASA with a $28 million budget, aimed to build 100 modules capable of reconfiguring for tasks like digging, exploration, and construction on other planets.
Each module in the Superbot project has three degrees of freedom for movement and six connectors for docking with other modules, running on a real-time operating system called avrx with infrared communication capabilities.
Modules can exhibit diverse locomotion, including individual movement, synchronized swimming, caterpillar-like crawling, rolling, and even climbing steep slopes or ropes.
Resilience is a key feature, with robots capable of maintaining function even if their body is cut in half, with the remaining parts adapting to form new configurations.
The 'digital hormones' control system uses content-based messages that trigger different actions across modules based on their current state and position, mimicking biological hormonal responses without explicit addressing or global identifiers.
The promise of polymorphic robotics
The polymorphic robotics lab focuses on creating self-reconfigurable systems, which are metamorphic robots capable of autonomously altering their logical and physical configurations, including shape, size, and formation. This adaptability allows them to change their locomotion and manipulation capabilities based on specific mission requirements and environmental conditions. The core advantages of such modular robots lie in their versatility, self-healing abilities, and cost-effective reproducibility, offering a flexible approach to tackling complex tasks in unstructured or dynamic environments. The lab's work, inspired by Professor Herbert Simon, a pioneer in artificial intelligence, explores how these robots can function effectively in scenarios where traditional, single-purpose robots would be insufficient or too expensive to deploy.
Early inspirations and the Superbot project
The lab's past projects included successful developments like the UDA robot for indoor navigation in 1996 and autonomous soccer robots that won the World Championship in Japan in 1997. Building on this foundation, the focus shifted to self-reconfigurable robots. The 'Superbot' project, initiated in 2004 with significant NASA sponsorship, aimed to develop a swarm of modular robots that could be deployed to extraterrestrial environments. The original vision was to pack 100 modules tightly, drop them onto a desert, have them reconfigure into a rolling track to find a sand dune, climb it, and then form a protective structure for seeds. Although budget cuts reduced the ambition to 20 modules and eliminated the desert deployment, the project highlighted the potential for advanced robotic systems in space exploration, construction, and maintenance.
Module design and capabilities
Each module in the Superbot project is designed with multiple degrees of freedom and several connectors, allowing for intricate movements and robust inter-module connections. Specifically, each module possesses three degrees of freedom for pitch and roll movements, with one rotational axis offering continuous movement and two side axes providing controlled rotation. They are equipped with six connectors located on the front, back, up, down, left, and right sides, enabling them to dock with up to six neighbors. Internally, these modules house microcontrollers running a real-time operating system (avrx), facilitating multi-threaded programming for tasks like motor control and communication. Each connector features infrared communication for inter-module interaction and sensing, alongside internal sensors such as 3D accelerometers for orientation detection and current/voltage sensors.
Diverse locomotion and configurations
A single module is itself a functional robot, capable of moving in various directions, including forward, backward, left, right, and even upside down. These modules can be programmed with complex gaits, some even discovered through genetic algorithms, leading to unique movements. When connected, modules can form an extensive array of configurations: long snakes, multi-legged creatures like centipedes or octopuses, chains, loops, and arbitrary tree structures. These configurations demonstrate remarkable locomotion capabilities. For instance, a six-legged caterpillar-like robot can move effectively, even on a beach with sandy conditions, and a chain configuration can move sideways or like a butterfly. The robots can also climb steep slopes, approaching 45 degrees, due to their low center of gravity and adaptive leg configurations.
Resilience and adaptive reconfiguration
A remarkable aspect of these self-reconfigurable robots is their resilience to physical disruption. They are designed to survive and adapt even when their bodies are deliberately sectioned. For example, if a robot is cut in half, both the front and rear sections can independently reconfigure themselves. One part might adapt to a two-legged butterfly motion if it senses it has only two legs remaining, while the other part does the same. If the parts are reconnected, or if the upper and lower bodies are swapped, the robots will reassess their configuration and adopt an appropriate movement strategy, such as reverting to a four-legged gait. This capability eliminates the need to shut down or reprogram the system after such an event, showcasing a high degree of autonomy and fault tolerance.
The 'digital hormones' control system
The control software for these robots is referred to as 'digital hormones,' drawing inspiration from biological hormonal systems. This approach emphasizes content-based, broadcast-like messages that float through the network of modules. These messages carry no explicit address or identifier but have a lifetime and trigger specific actions based on the receiving module's identity, location, and current state. For instance, a single 'fear' hormone message might cause legs to jump, eyes to widen, and mouths to open in a biological system. Similarly, in the robots, one signal can lead to different behaviors across modules—some might move, others might engage in communication. This distributed control mechanism operates without a global clock or unique identifiers for each module, allowing the system to adapt and function even when modules are added, removed, or when the network topology changes dynamically.
Technical challenges and future directions
Developing effective control software for self-reconfigurable robots presents several significant challenges. These include the absence of a fixed 'brain' or global identifiers, the need for task negotiation and behavior selection based on local context, handling dynamic network topologies, and managing asynchronous communication due to independent module clocks. Scalability is also crucial, as the software must adapt to an unpredictable range of shapes and sizes. The 'digital hormones' system aims to address these by enabling modules to infer their position and role within the overall structure and act accordingly. Future work focuses on enabling autonomous shape determination for specific tasks, such as reaching for an object, and expanding applications in areas like search and rescue, space assembly, and self-healing structures.
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Common Questions
Self-reconfigurable robots are systems capable of changing their shape and size autonomously based on their environment and required tasks. They are composed of smaller modules that can connect and disconnect to form various configurations.
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Mentioned in this video
A graduate student in the lab.
A PhD student in the lab, credited with discovering a 'junking' movement for single modules and working on rope climbing.
A graduate student in the lab who demonstrated a robot module's ability to carry a cup without spilling and worked on the Coke-drinking experiment.
The speaker's advisor, a Nobel Prize winner for economics and a father of artificial intelligence, who passed away in 2011.
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