This paper proposes a strategy for transporting a large object to a goal using a large number of mobile robots that are significantly smaller than the object. The robots only push the object at positions where the direct line of sight to the goal is occluded by the object. This strategy is fully decentralized and requires neither explicit communication nor specific manipulation mechanisms. We prove that it can transport any convex object in a planar environment. We implement this strategy on the e-puck robotic platform and present systematic experiments with a group of 20 e-pucks transporting three objects of different shapes. The objects were successfully transported to the goal in 43 out of 45 trials. When using a mobile goal, teleoperated by a human, the object could be navigated through an environment with obstacles. We also tested the strategy in a 3-D environment using physics-based computer simulation. Due to its simplicity, the transport strategy is particularly suited for implementation on microscale robotic systems.
A canonical problem for swarms of agents is to collectively choose one of multiple options in their environment. We present a novel control strategy for solving this problemthe first to be free of arithmetic computation. The agents do not communicate with each other nor do they store run-time information. They have a line-of-sight sensor that extracts one ternary digit of information from the environment. At every time step, they directly map this information onto constant-value motor commands. We evaluate the control strategy with both simulated and physical e-puck robots. By default, the robots are expected to choose, and move to, one of two options of equal value. The simulation studies show that the strategy is robust against sensory noise, scalable to large swarm sizes, and generalizes to the problems of choosing between more than two options or between unequal options. The experiments-50 trials conducted with a group of 20 e-puck robots-show that the group achieves consensus in 96% of the trials. Given the extremely low hardware requirements of the strategy, it opens up new possibilities for the design of swarms of robots that are small in size ( 10 −3 m) and large in numbers ( 10 3 ).
We study the problem of controlling a swarm of anonymous, mobile robots to cooperatively cover an unknown two-dimensional space. The novelty of our proposed solution is that it is applicable to extremely simple robots that lack run-time computation or storage. The solution requires only a single bit of information per robot-whether or not another robot is present in its line of sight. Computer simulations show that our deterministic controller, which was obtained through off-line optimization, achieves around 71-76% coverage in a test scenario with no robot redundancy, which corresponds to a 26-39% reduction of the area that is not covered, when compared to an optimized random walk. A moderately lower level of performance was observed in 20 experimental trials with 25 physical e-puck robots. Moreover, we demonstrate that the same controller can be used in environments of different dimensions and even to navigate a maze. The controller provides a baseline against which one can quantify the performance improvements that more advanced and expensive techniques may offer. Moreover, due to its simplicity, it could potentially be implemented on swarms of sub-millimeter-sized robots. This would pave the way for new applications in micro-medicine.
This is a repository copy of Decentralized pose control of modular reconfigurable robots operating in liquid environments.
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