There are many ways to implement programmable matter. One is to build it as a huge modular selfreconfigurable robot composed of a large set of spherical micro-robots, like in the Claytronics project. These micro-robots must be able to stick to each other and move around each other. However, the shape of these micro-robots has not been studied yet and remains a difficult problem as there are numerous constraints to respect. In this article, we propose a quasi-spherical structure for these micro-robots, which answers all the constraints for building programmable matter, helping the realization of an interactive computer-aided design (CAD) framework. We study different scenarios, validate the ability to move and propose methods for manufacturing these micro-robots.
This paper presents a distributed control architecture to perform part recognition and closed-loop control of a distributed manipulation device. This architecture is based on decentralized cells able to communicate with their four neighbors thanks to peer-to-peer links. Various original algorithms are proposed to reconstruct, recognize and convey the object levitating on a new contactless distributed manipulation device. Experimental results show that each algorithm does a good job for itself and that all the algorithms together succeed in sorting and conveying the objects to their final destination. In the future, this architecture may be used to control MEMS-arrayed manipulation surfaces in order to develop Smart Surfaces, for conveying, fine positioning and sorting of very small parts for micro-systems assembly lines.
Programmable matter i.e. matter that can change its physical properties, more likely its shape according to an internal or an external action is a good example of a cybermatics component. As it links a cyberized shape to real matter, it is a straight example of cyber-physical conjugation. But, this interaction between virtual and real worlds needs two elements. The first one is to find a way to represent the cyberized object using programmable matter and the second is to be able to adapt the matter to the cyberized changes. This article presents the progresses made in these two topics within the Claytronics project.
Modularity and self-healing are two interesting properties that could help to design more flexible conveyors of micro-objects. In the Smart Blocks project, we propose to design a 2D modular and self-reconfigurable robot composed of centimeter-scale sliding blocks that embed their own actuators and control electronics. This article presents a proof-of-concept of the linkage and of the traveling system as well as an algorithm able to reconfigure a set of blocks from a spatial configuration to another one. Prototype blocks have been realized using electro-permanent magnets which show a good motion speed while saving power consumption during the linkage. Our reconfiguration algorithm is implemented in a simulator software showing in real-time the reconfiguration of the robot.
MEMS research has until recently focused mainly on the engineering process, resulting in interesting products and a growing market. To fully realize the promise of MEMS, the next step is to add embedded intelligence. With embedded intelligence, the scalability of manufacturing will enable distributed MEMS systems consisting of thousands or millions of units which can work together to achieve a common goal. However, before such systems can become a reallity, we must come to grips with the challenge of scalability which will require paradigm-shifts both in hardware and software. Furthermore, the need for coordinated actuation, programming, communication and mobility management raises new challenges in both control and programming. The objective of this article is to report the progresses made by taking the example of two research projects and by giving the remaining challenges and the perspectives of distributed intelligent MEMS.
Modular self-reconfigurable robots are composed of independent connected modules which can self-rearrange their connectivity using processing, communication and motion capabilities, in order to change the overall robot structure. In this paper, we consider rolling cylindrical modules arranged in a two-dimensional vertical hexagonal lattice. We propose a parallel, asynchronous and fully decentralized distributed algorithm to self-reconfigure robots from an initial configuration to a goal one. We evaluate our algorithm on the millimeter-scale cylindrical robots, developed in the Claytronics project, through simulation of large ensembles composed of up to ten thousand modules. We show the effectiveness of our algorithm and study its performance in terms of communications, movements and execution time. Our observations indicate that the number of communications, the number of movements and the execution time of our algorithm is highly predictable. Furthermore, we observe execution times that are linear in the size of the goal shape.
Adaptation control of beamforming interference cancellation techniques is investigated for in-car speech acquisition. Two efficient adaptation control methods are proposed that avoid target cancellation. The "implicit" method varies the step-size continuously, based on the filtered output signal. The "explicit" method decides in a binary manner whether to adapt or not, based on a novel estimate of target and interference energies. It estimates the average delay-sum power within a volume of space, for the same cost as the classical delay-sum. Experiments on real in-car data validate both methods, including a case with 100 km/h background road noise.
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