GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

A robot swarm assisting a human fire-fighter

Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings

Multi-robot behaviors with bearing-only sensors and scale-free coordinates

This thesis presents a low-cost multi-robot system for large populations of robots, a new coordinate system for the robot based on angles between robots and a series of experiments validating robot performance. The new robot platform, the r-one will serve as an educational, outreach and research platform for robotics. I consider the robot's bearing-only sensor model, where each robot is capable of measuring the bearing, but not the distance, to each of its neighbors. This work also includes behaviors demonstrating the efficiency of this approach with this bearing-only sensor model. The new local coordinate systems based on angular information is introduced as scale-free coordinate system . Each robot produces its own local scale-free coordinates to determine the relative positions of its neighbors up to an unknown scaling factor. The computation of scale-free coordinates is analyzed with hardware and simulation validation. For hardware, the scale-free algorithm is tailored to low-cost systems with limited communication bandwidth and sensor resolution. The algorithm also uses a noise sensitivity model to reduce the impact of noise on the computed scale-free coordinates. I validate the algorithm with static and dynamic motion experiments

GUARDIANS final report part 1 (draft): a robot swarm assisting a human fire fighter

Emergencies in industrial warehouses are a major concern for fire fighters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist re ghters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting re ghters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus the robot swarm is able to provide guidance information to the humans. Together with the fire fighters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

Evolving robots: from simple behaviours to complete systems

Building robots is generally considered difficult, because the designer not only has to predict the interaction between the robot and the environment, but also has to deal with the ensuing problems. This thesis examines the use of the evolutionary approach in designing robots; the explorations range from evolving simple behaviours for real robots, to complex behaviours (also for real robots), and finally to complete robot systems — including controllers and body plans. A framework is presented for evolving robot control systems. It includes two components: a task independent Genetic Programming sub-system and a task dependent controller evaluation sub-system. The performance evaluation of each robot controller is done in a simulator to reduce the evaluation time, and then the evolved controllers are downloaded to a real robot for performance verification. In addition, a special rep¬ resentation is designed for the reactive robot controller. It is succinct and can capture the important characteristics of a reactive control system, so that the evolutionary system can efficiently evolve the controllers of the desired behaviours for the robots. The framework has been successfully used to evolve controllers for real robots to achieve a variety of simple tasks, such as obstacle avoidance, safe exploration and box-pushing. A methodology is then proposed to scale up the system to evolve controllers for more complicated tasks. It involves adopting the architecture of a behaviour-based system, and evolving separate behaviour controllers and arbitrators for coordination. This allows robot controllers for more complex skills to be constructed in an incremental manner. Therefore the whole control system becomes easy to evolve; moreover, the resulting control system can be explicitly distributed, understandable to the system designer, and easy to maintain. The methodology has been used to evolve control systems for more complex tasks with good results. Finally, the evolutionary mechanism of the framework described above is extended to include a Genetic Algorithm sub-system for the co-evolution of robot body plans — structuralparametersofphysicalrobotsencodedaslinearstringsofrealnumbers. An individual in the extended system thus consists of a brain(controller) and a body. Whenever the individual is evaluated, the controller is executed on the corresponding body for a period of time to measure the performance. In such a system the Genetic Programming part evolves the controller; and the Genetic Algorithm part, the robot body. The results show that the complete robot system can be evolved in this manner. i

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

In this paper, a review on the three most important communication techniques (ground, aerial, and underwater vehicles) has been presented that throws light on trajectory planning, its optimization, and various issues in a summarized way. This kind of extensive research is not often seen in the literature, so an effort has been made for readers interested in path planning to fill the gap. Moreover, optimization techniques suitable for implementing ground, aerial, and underwater vehicles are also a part of this review. This paper covers the numerical, bio-inspired techniques and their hybridization with each other for each of the dimensions mentioned. The paper provides a consolidated platform, where plenty of available research on-ground autonomous vehicle and their trajectory optimization with the extension for aerial and underwater vehicles are documented

Classification and Management of Computational Resources of Robotic Swarms and the Overcoming of their Constraints

Swarm robotics is a relatively new and multidisciplinary research field with many potential applications (e.g., collective exploration or precision agriculture). Nevertheless, it has not been able to transition from the academic environment to the real world. While there are many potential reasons, one reason is that many robots are designed to be relatively simple, which often results in reduced communication and computation capabilities. However, the investigation of such limitations has largely been overlooked. This thesis looks into one such constraint, the computational constraint of swarm robots (i.e., swarm robotics platform). To achieve this, this work first proposes a computational index that quantifies computational resources. Based on the computational index, a quantitative study of 5273 devices shows that swarm robots provide fewer resources than many other robots or devices. In the next step, an operating system with a novel dual-execution model is proposed, and it has been shown that it outperforms the two other robotic system software. Moreover, results show that the choice of system software determines the computational overhead and, therefore, how many resources are available to robotic software. As communication can be a key aspect of a robot's behaviour, this work demonstrates the modelling, implementing, and studying of an optical communication system with a novel dynamic detector. Its detector improves the quality of service by orders of magnitude (i.e., makes the communication more reliable). In addition, this work investigates general communication properties, such as scalability or the effects of mobility, and provides recommendations for the use of such optical communication systems for swarm robotics. Finally, an approach is shown by which computational constraints of individual robots can be overcome by distributing data and processing across multiple robots

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Self–organised multi agent system for search and rescue operations

Autonomous multi-agent systems perform inadequately in time critical missions, while they tend to explore exhaustively each location of the field in one phase with out selecting the pertinent strategy. This research aims to solve this problem by introducing a hierarchy of exploration strategies. Agents explore an unknown search terrain with complex topology in multiple predefined stages by performing pertinent strategies depending on their previous observations. Exploration inside unknown, cluttered, and confined environments is one of the main challenges for search and rescue robots inside collapsed buildings. In this regard we introduce our novel exploration algorithm for multi–agent system, that is able to perform a fast, fair, and thorough search as well as solving the multi–agent traffic congestion. Our simulations have been performed on different test environments in which the complexity of the search field has been defined by fractal dimension of Brownian movements. The exploration stages are depicted as defined arenas of National Institute of Standard and Technology (NIST). NIST introduced three scenarios of progressive difficulty: yellow, orange, and red. The main concentration of this research is on the red arena with the least structure and most challenging parts to robot nimbleness

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described