Cooperation through self-assembly in multi-robot

This article illustrates the methods and results of two sets of experiments in which a group of mobile robots, called s-bots, are required to physically connect to each other, that is, to self-assemble, to cope with environmental conditions that prevent them from carrying out their task individually. The first set of experiments is a pioneering study on the utility of self-assembling robots to address relatively complex scenarios, such as cooperative object transport. The results of our work suggest that the s-bots possess hardware characteristics which facilitate the design of control mechanisms for autonomous self-assembly. The control architecture we developed proved particularly successful in guiding the robots engaged in the cooperative transport task. However, the results also showed that some features of the robots’ controllers had a disruptive effect on their performances. The second set of experiments is an attempt to enhance the adaptiveness of our multi-robot system. In particular, we aim to synthesise an integrated (i.e., not-modular) decisionmaking mechanism which allows the s-bot to autonomously decide whether or not environmental contingencies require self-assembly. The results show that it is possible to synthesize, by using evolutionary computation techniques, artificial neural networks that integrate both the mechanisms for sensory-motor coordination and for decision making required by the robots in the context of self-assembly

Influence of self-disassembly of bridges on collective flow characteristics of swarm robots in a single-lane and periodic system with a gap

Inspired by the living bridges formed by ants, swarm robots have been developed to self-assemble bridges to span gaps and self-disassemble them. Self-disassembly of bridges may increase the transport efficiency of swarm robots by increasing the number of moving robots, and also may decrease the efficiency by causing gaps to reappear. Our aim is to elucidate the influence of self-disassembly of bridges on the collective flow characteristics of swarm robots in a single-lane and periodic system with a gap. In the system, robots span and cross the gap by self-assembling a single-layer bridge. We consider two scenarios in which self-disassembling bridges is prevented (prevent-scenario) or allowed (allow-scenario). We represent the horizontal movement of robots with a typical car-following model, and simply model the actions of robots for self-assembling and self-disassembling bridges. Numerical simulations have revealed the following results. Flow-density diagrams in both the scenarios shift to the higher-density region as the gap length increases. When density is low, allow-scenario exhibits the steady state of repeated self-assembly and self-disassembly of bridges. If density is extremely low, flow in this state is greater than flow in prevent-scenario owing to the increase in the number of robots moving horizontally. Otherwise, flow in this state is smaller than flow in prevent-scenario. Besides, flow in this state increases monotonically with respect to the velocity of robots in joining and leaving bridges. Thus, self-disassembling bridges is recommended for only extremely low-density conditions in periodic systems. This study contributes to the development of the collective dynamics of self-driven particles that self-assemble structures, and stirs the dynamics with other self-assembled structures, such as ramps, chains, and towers.Comment: 13 pages, 9 figure

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA

Path Planning of Mobile Agents using AI Technique

In this paper, we study coordinated motion in a swarm robotic system, called a swarm-bot. A swarm-bot is a self-assembling and self-organizing. Artifact composed of a swarm of s-bots, mobile robots with the ability to connect to and is connect from each other. The swarm-bot concept is particularly suited for tasks that require all-terrain navigation abilities, such as space exploration or rescue in collapsed buildings. As a first step toward the development of more complex control strategies, we investigate the case in which a swarm-bot has to explore an arena while avoiding falling into holes. In such a scenario, individual s-bots have sensory–motor limitations that prevent them navigating efficiently. These limitations can be overcome if the s-bots are made to cooperate. In particular, we exploit the s-bots’ ability to physically connect to each other. In order to synthesize the s-bots’ controller, we rely on artificial evolution, which we show to be a powerful tool for the production of simple and effective solutions to the hole avoidance task

Grasping and Assembling with Modular Robots

A wide variety of problems, from manufacturing to disaster response and space exploration, can benefit from robotic systems that can firmly grasp objects or assemble various structures, particularly in difficult, dangerous environments. In this thesis, we study the two problems, robotic grasping and assembly, with a modular robotic approach that can facilitate the problems with versatility and robustness. First, this thesis develops a theoretical framework for grasping objects with customized effectors that have curved contact surfaces, with applications to modular robots. We present a collection of grasps and cages that can effectively restrain the mobility of a wide range of objects including polyhedra. Each of the grasps or cages is formed by at most three effectors. A stable grasp is obtained by simple motion planning and control. Based on the theory, we create a robotic system comprised of a modular manipulator equipped with customized end-effectors and a software suite for planning and control of the manipulator. Second, this thesis presents efficient assembly planning algorithms for constructing planar target structures collectively with a collection of homogeneous mobile modular robots. The algorithms are provably correct and address arbitrary target structures that may include internal holes. The resultant assembly plan supports parallel assembly and guarantees easy accessibility in the sense that a robot does not have to pass through a narrow gap while approaching its target position. Finally, we extend the algorithms to address various symmetric patterns formed by a collection of congruent rectangles on the plane. The basic ideas in this thesis have broad applications to manufacturing (restraint), humanitarian missions (forming airfields on the high seas), and service robotics (grasping and manipulation)

Hardware Architecture Review of Swarm Robotics System: Self-Reconfigurability, Self-Reassembly, and Self-Replication

Swarm robotics is one of the most fascinating and new research areas of recent decades, and one of the grand challenges of robotics is the design of swarm robots that are self-sufficient. This can be crucial for robots exposed to environments that are unstructured or not easily accessible for a human operator, such as the inside of a blood vessel, a collapsed building, the deep sea, or the surface of another planet. In this paper, we present a comprehensive study on hardware architecture and several other important aspects of modular swarm robots, such as self-reconfigurability, self-replication, and self-assembly. The key factors in designing and building a group of swarm robots are cost and miniaturization with robustness, flexibility, and scalability. In robotics intelligence, self-assembly and self-reconfigurability are among the most important characteristics as they can add additional capabilities and functionality to swarm robots. Simulation and model design for swarm robotics is highly complex and expensive, especially when attempting to model the behavior of large swarm robot groups.http://dx.doi.org/10.5402/2013/84960

Kinetic Blocks: Actuated Constructive Assembly for Interaction and Display

Pin-based shape displays not only give physical form to digital information, they have the inherent ability to accurately move and manipulate objects placed on top of them. In this paper we focus on such object manipulation: we present ideas and techniques that use the underlying shape change to give kinetic ability to otherwise inanimate objects. First, we describe the shape display's ability to assemble, disassemble, and reassemble structures from simple passive building blocks through stacking, scaffolding, and catapulting. A technical evaluation demonstrates the reliability of the presented techniques. Second, we introduce special kinematic blocks that are actuated and sensed through the underlying pins. These blocks translate vertical pin movements into other degrees of freedom like rotation or horizontal movement. This interplay of the shape display with objects on its surface allows us to render otherwise inaccessible forms, like overhangs, and enables richer input and output

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics