Illustration: JPL-Caltech/NASA In our previous newsletters, we talked about how scientists used Kilobots and Khepera IV as study robots to make their research on robotics and autonomous systems. Different topics were highlighted these last months such as local communication, augmented reality, robot’s state and location, swarm robotics, multi-robot navigation, and collective movements. All these diverse […]
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The Kilobot is designed to make tests of collective algorithms on hundreds or thousands of robots accessible to robotics researchers.
Though the Kilobots are low-cost, they maintain abilities similar to other collective robots. These abilities include differential drive locomotion, on-board computation power, neighbor-to-neighbor communication, neighbor-to-neighbor distance sensing, and ambient light sensing.
The Khepera IV is a compact robot designed for any indoor lab application (table, lab floor). Compact, it requires a small space to operate, even in swarm. With its high flexibility, the Khepera IV robot can almost make any application such as navigation, swarm, artificial intelligence, computation, demonstration, etc . Thanks to the KB-250 bus which allows you to stack many different extensions in a few seconds on the top of the robot, providing an unbeatable modularity.
The Koala is a mid-size robot designed for real-world applications. Bigger than Khepera, more powerful, and capable of carrying larger accessories.
Koala has the functionality necessary for use in various applications such as navigation, swarm, artificial intelligence, computation, demonstration, etc. It rides on 6 wheels for indoor all-terrain operation, and sports stylish bodywork for attractive demonstrations.
Khepera IV robots help to study multi-robot navigation and collective movements
/0 Comments/in News1 /by kteamIn the newsletter of March 2022, we would like to highlight the research work of Baumann&Martinoli, 2021 published in Robotics and Autonomous Systems (https://doi.org/10.1016/j.robot.2021.103849). In this study, they leveraged Khepera IV robots and studied the design of tightly integrated allocation, control, and estimation algorithms enabling coordinated movements of a group of robots. They validated their algorithms through simulation and physical experiments, showing the design effectiveness of their modular framework based on functional elements. Furthermore, thanks to the developed modular framework, they explored the impact of localization and communication constraints on the collective movement performance of the multi-robot system. In conclusion, algorithm benchmarking is more operational when defining modularity based on functionality. Safely moving a group of robots following specific requirements (e.g. as a flock or formation) is one of the basic and yet essential component needed for multi-vehicle applications such as space coverage and exploration, search and rescue scenarios, and management of transportation systems. Investigating collective movements through Khepera IV mobile robots is one effective way to tackle hard multi-vehicle coordination challenges in the physical world.