Large scale MEMS robots cooperative map building based on realistic simulation of nano-wireless communications

International audienceThe Claytronics project has produced interesting hardware components like cylindric micro-robots called catoms and software models to enable the concept of programmable matter. One application is the use of several catoms linked together so that they can " walk ". These walkers can explore an area and thanks to electromagnetic wireless nano-networks, they can communicate with each other sharing the map of the place to explore. In this paper, we study the different parameters influencing the transmission quality of the map to a sink which uses both traditional wireless and wireless nano-communication networks

Self-organized aggregation without computation

This paper presents a solution to the problem of self-organized aggregation of embodied robots that requires no arithmetic computation. The robots have no memory and are equipped with one binary sensor, which informs them whether or not there is another robot in their line of sight. It is proven that the sensor needs to have a sufficiently long range; otherwise aggregation cannot be guaranteed, irrespective of the controller used. The optimal controller is found by performing a grid search over the space of all possible controllers. With this controller, robots rotate on the spot when they perceive another robot, and move backwards along a circular trajectory otherwise. This controller is proven to always aggregate two simultaneously moving robots in finite time, an upper bound for which is provided. Simulations show that the controller also aggregates at least 1000 robots into a single cluster consistently. Moreover, in 30 experiments with 40 physical e-puck robots, 98.6% of the robots aggregated into one cluster. The results obtained have profound implications for the implementation of multi-robot systems at scales where conventional approaches to sensing and information processing are no longer applicable

A Hybrid and Extendable Self-Reconfigurable Modular Robotic System

Modular robotics has the potential to transform the perception of robotic systems from machines built for specific tasks to multi-purpose tools capable of performing virtually any task. This thesis presents the design, implementation and study of a new self-reconfigurable modular robotic system for use as a research and education platform. The system features a high-speed genderless connector (HiGen), a hybrid module (HyMod), an extensions framework, and a control architecture. The HiGen connector features inter-module communication and is able to join with other HiGen connectors in a manner that allows either side to disconnect in the event of failure. The rapid actuation of HiGen allows connections to be made and broken at a speed that is, to our knowledge, an order of magnitude faster than existing mechanical genderless approaches that feature single-sided disconnect, benefiting the self-reconfiguration time of modular robots. HyMod is a chain, lattice, and mobile hybrid modular robot, consisting of a spherical joint unit that is capable of moving independently and grouping with other units to form arbitrary cubic lattice structures. HyMod is the first module, to our knowledge, that combines efficient single-module locomotion, enabling self-assembly, with the ability for modules to freely rotate within their lattice positions, aiding the self-reconfigurability of large structures. The extension framework is used to augment the capabilities of HyMod units. Extensions are modules that feature specialized functionality, and interface with HyMod units via passive HiGen connectors, allowing them to be un-powered until required for a task. Control of the system is achieved using a software architecture. Based on message routing, the architecture allows for the concurrent use of both centralized and distributed module control strategies. An analysis of the system is presented, and experiments conducted to demonstrate its capabilities. Future versions of the system created by this thesis could see uses in reconfigurable manufacturing, search and rescue, and space exploration

Swarm Robotic Systems with Minimal Information Processing

This thesis is concerned with the design and analysis of behaviors in swarm robotic systems using minimal information acquisition and processing. The motivation for this work is to contribute in paving the way for the implementation of swarm robotic systems at physically small scales, which will open up new application domains for their operation. At these scales, the space and energy available for the integration of sensors and computational hardware within the individual robots is at a premium. As a result, trade-offs in performance can be justified if a task can be achieved in a more parsimonious way. A framework is developed whereby meaningful collective behaviors in swarms of robots can be shown to emerge without the robots, in principle, possessing any run-time memory or performing any arithmetic computations. This is achieved by the robots having only discrete-valued sensors, and purely reactive controllers. Black-box search methods are used to automatically synthesize these controllers for desired collective behaviors. This framework is successfully applied to two canonical tasks in swarm robotics: self-organized aggregation of robots, and self-organized clustering of objects by robots. In the case of aggregation, the robots are equipped with one binary sensor, which informs them whether or not there is another robot in their line of sight. This makes the structure of the robots’ controller simple enough that its entire space can be systematically searched to locate the optimal controller (within a finite resolution). In the case of object clustering, the robots’ sensor is extended to have three states, distinguishing between robots, objects, and the background. This still requires no run-time memory or arithmetic computations on the part of the robots. It is statistically shown that the extension of the sensor to have three states leads to a better performance as compared to the cases where the sensor is binary, and cannot distinguish between robots and objects, or robots and the background

Shape formation by self-disassembly in programmable matter systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 225-236).Programmable matter systems are composed of small, intelligent modules able to form a variety of macroscale objects with specific material properties in response to external commands or stimuli. While many programmable matter systems have been proposed in fiction, (Barbapapa, Changelings from Star Trek, the Terminator, and Transformers), and academia, a lack of suitable hardware and accompanying algorithms prevents their full realization. With this thesis research, we aim to create a system of miniature modules that can form arbitrary structures on demand. We develop autonomous 12mm cubic modules capable of bonding to, and communicating with, four of their immediate neighbors. These modules are among the smallest autonomous modular robots capable of sensing, communication, computation, and actuation. The modules employ unique electropermanent magnet connectors. The four connectors in each module enable the modules to communicate and share power with their nearest neighbors. These solid-state connectors are strong enough for a single inter-module connection to support the weight of 80 other modules. The connectors only consume power when switching on or off; they have no static power consumption. We implement a number of low-level communication and control algorithms which manage information transfer between neighboring modules. These algorithms ensure that messages are delivered reliably despite challenging conditions. They monitor the state of all communication links and are able to reroute messages around broken communication links to ensure that they reach their intended destinations. In order to accomplish our long-standing goal of programmatic shape formation, we also develop a suite of provably-correct distributed algorithms that allow complex shape formation. The distributed duplication algorithm that we present allows the system to duplicate any passive object that is submerged in a collection of programmable matter modules. The algorithm runs on the processors inside the modules and requires no external intervention. It requires 0(1) storage and O(n) inter-module messages per module, where n is the number of modules in the system. The algorithm can both magnify and produce multiple copies of the submerged object. A programmable matter system is a large network of autonomous processors, so these algorithms have applicability in a variety of routing, sensor network, and distributed computing applications. While our hardware system provides a 50-module test-bed for the algorithms, we show, by using a unique simulator, that the algorithms are capable of operating in much larger environments. Finally, we perform hundreds of experiments using both the simulator and hardware to show how the algorithms and hardware operate in practice.by Kyle William Gilpin.Ph.D