Real-time software for mobile robot simulation and experimentation in cooperative environments

Trabajo presentado al 1st SIMPAR celebrado en Venecia del 3 al 6 de noviembre de 2008.This paper presents the software being developed at IRI (Institut de Robotica i Informatica Industrial) for mobile robot autonomous navigation in the context of the European project URUS (Ubiquitous Robots in Urban Settings). In order that a deployed sensor network and robots operating in the environment cooperate in terms of information sharing, main requirements are real-time performance and the integration of information coming from remote machines not onboard the robot. Moreover, the project involves a group of eleven industrial and academic partners, therefore software integration issues are critical. The proposed software framework is based on the YARP middleware and has been tested in real and simulated experiments.This work was supported by projects: 'Ubiquitous networking robotics in urban settings' (E-00938), 'CONSOLIDER-INGENIO 2010 Multimodal interaction in pattern recognition and computer vision' (V-00069), 'Robotica ubicua para entornos urbanos' (J-01225). Partially supported by Consolider Ingenio 2010, project CSD2007-00018, CICYT project DPI2007-61452, and IST-045062 of the European Community Union.Peer Reviewe

Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

Experimental Testbed for Large Multirobot Teams

Experimental validation is particularly important in multirobot systems research. The differences between models and real-world conditions that may not be apparent in single robot experiments are amplified because of the large number of robots, interactions between robots, and the effects of asynchronous and distributed control, sensing, and actuation. Over the last two years, we have developed an experimental testbed to support research in multirobot systems with the goal of making it easy for users to model, design, benchmark, and validate algorithms. In this article, we describe our approach to the design of a large-scale multirobot system for the experimental verification and validation of a variety of distributed robotic applications in an indoor environment

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

MULTI-ROBOT COVERAGE WITH DYNAMIC COVERAGE INFORMATION COMPRESSION

This work considers the problem of coverage of an initially unknown environment by a set of autonomous robots. A crucial aspect in multi-robot coverage involves robots sharing information about the regions they have already covered at certain intervals, so that multiple robots can avoid repeated coverage of the same area. However, sharing the coverage information between robots imposes considerable communication and computation overhead on each robot, which increases the robots’ battery usage and overall coverage time. To address this problem, we explore a novel coverage technique where robots use an information compression algorithm before sharing their coverage maps with each other. Specifically, we use a polygonal approximation algorithm to represent any arbitrary region covered by a robot as a polygon with a fixed, small number of vertices. At certain intervals, each robot then sends this small set of vertices to other robots in its communication range as its covered area, and each receiving robot records this information in a local map of covered regions so that it can avoid repeat coverage. The coverage information in the map is then utilized by a technique called spanning tree coverage (STC) by each robot to perform area coverage. We have verified the performance of our algorithm on simulated Coroware Corobot robots within the Webots robot simulator with different sizes of environments and different types of obstacles in the environments, while modelling sensor noise from the robots’ sensors. Our results show that using the polygonal compression technique is an effective way to considerably reduce data transfer between robots in a multi-robot team without sacrificing the performance and efficiency gains that communication provides to such a system

Swarm robotics: Cooperative navigation in unknown environments

Swarm Robotics is garnering attention in the robotics field due to its substantial benefits. It has been proven to outperform most other robotic approaches in many applications such as military, space exploration and disaster search and rescue missions. It is inspired by the behavior of swarms of social insects such as ants and bees. It consists of a number of robots with limited capabilities and restricted local sensing. When deployed, individual robots behave according to local sensing until the emergence of a global behavior where they, as a swarm, can accomplish missions individuals cannot. In this research, we propose a novel exploration and navigation method based on a combination of Probabilistic Finite Sate Machine (PFSM), Robotic Darwinian Particle Swarm Optimization (RDPSO) and Depth First Search (DFS). We use V-REP Simulator to test our approach. We are also implementing our own cost effective swarm robot platform, AntBOT, as a proof of concept for future experimentation. We prove that our proposed method will yield excellent navigation solution in optimal time when compared to methods using either PFSM only or RDPSO only. In fact, our method is proved to produce 40% more success rate along with an exploration speed of 1.4x other methods. After exploration, robots can navigate the environment forming a Mobile Ad-hoc Network (MANET) and using the graph of robots as network nodes

ARENA—augmented reality to enhanced experimentation in smart warehouses

The current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems and failures that may only exist in real situations. This work presents an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements. The concept of ARENA introduces a novel approach to realistic and immersive experimentation in industrial environments, aiming to evaluate new technologies aligned with the Industry 4.0. The proposed method consists of a small-scale warehouse, inspired in a real scenario characterized in this paper, managing by a group of autonomous forklifts, fully interconnected, which are embodied by a swarm of tiny robots developed and prepared to operate in the small scale scenario. The AR is employed to enhance the capabilities of swarm robots, allowing box handling and virtual forklifts. Virtual laser range finders (LRF) are specially designed as segmentation of a global RGB-D camera, to improve robot perception, allowing obstacle avoidance and environment mapping. This infrastructure enables the evaluation of new strategies to improve manufacturing productivity, without compromising the production by automation faults.info:eu-repo/semantics/publishedVersio