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Tiny robots, ranging in size from tens to a few hundred grams, are gaining popularity for their versatility and potential applications in various fields. But, how do these small, autonomous robots navigate their environment with limited resources? The answer lies in inspired techniques from nature, specifically ant behavior.
Learning from Nature: Step Counting and Visual Snapshots
Researchers at TU Delft have developed an autonomous navigation strategy inspired by the way ants recognize their surroundings and count their steps. This approach allows small, lightweight robots to return home after long journeys, using minimal computation and memory (only 0.65 kilobyte per 100 meters). Such robots could potentially be used for tasks like warehouse stock monitoring, greenhouse crop monitoring, and detecting gas leaks.
Autonomous Navigation Challenge
The biggest challenge facing tiny robots is operating autonomously without relying on external infrastructure, which may not be available or feasible. GPS satellites can be inaccurate, while setting up beacons can be expensive. Traditional AI designed for larger robots also relies on heavy, power-intensive sensors, which are unsuitable for small robots. Additionally, vision-based approaches require detailed 3D maps of the environment, consuming significant processing power and memory.
Fascinating Insect Biology
Insects, despite their limited sensing and computing resources, effectively navigate over distances relevant to many applications. One theory, the “snapshot” model, suggests insects take periodic visual snapshots of their environment and use them to navigate by minimizing visual differences. This concept is similar to Hansel’s method in the fairy tale, where stones dropped on the ground served as markers.
Robot Solution
The researchers demonstrated their strategy with a 56-gram “CrazyFlie” drone equipped with an omnidirectional camera, successfully covering distances up to 100 meters using only 0.65 kilobyte of memory. All visual processing was done on a small micro-controller. “Spacing snapshots further apart is possible if the robot uses odometry between snapshots, which allows the robot to travel further,” explains Guido de Croon.
Practical Applications
This navigation strategy has significant implications for the development of practical applications. For instance, warehouse drones could collect data and return to a base station, storing mission-relevant images on a small SD card for later analysis.
Related Links
Delft University of Technology
All about the robots on Earth and beyond!
Tiny autonomous robots, inspired by nature’s incredible navigation abilities, have the potential to transform various industries. With the proposed strategy, these small robots can travel efficiently and accurately, making them a game-changer for tasks like monitoring inventory, detecting gas leaks, and more.
Frequently Asked Questions
What are tiny autonomous robots?
Tiny autonomous robots are small, lightweight robots, often weighing tens to hundreds of grams, designed to operate independently in a variety of environments.
Why is navigation a challenge for these robots?
Navigation is challenging for tiny autonomous robots due to their limited resources, including computation, memory, and sensor capabilities.
What technology did the researchers use in the experiment?
The researchers used an omnidirectional camera-equipped “CrazyFlie” drone with a 56-gram weight, demonstrating successful autonomous navigation up to 100 meters using only 0.65 kilobytes of memory.
How will these robots be used in real-world applications?
These robots could be used in applications such as warehouse stock monitoring, greenhouse crop monitoring, detecting gas leaks, and more.
What is the potential of tiny robots for future applications?
Tiny autonomous robots have the potential to revolutionize industries by providing efficient, cost-effective solutions for tasks that require precision, versatility, and adaptability.
