Efficient Multi-Robot Coverage of a Known Environment

This paper addresses the complete area coverage problem of a known environment by multiple-robots. Complete area coverage is the problem of moving an end-effector over all available space while avoiding existing obstacles. In such tasks, using multiple robots can increase the efficiency of the area coverage in terms of minimizing the operational time and increase the robustness in the face of robot attrition. Unfortunately, the problem of finding an optimal solution for such an area coverage problem with multiple robots is known to be NP-complete. In this paper we present two approximation heuristics for solving the multi-robot coverage problem. The first solution presented is a direct extension of an efficient single robot area coverage algorithm, based on an exact cellular decomposition. The second algorithm is a greedy approach that divides the area into equal regions and applies an efficient single-robot coverage algorithm to each region. We present experimental results for two algorithms. Results indicate that our approaches provide good coverage distribution between robots and minimize the workload per robot, meanwhile ensuring complete coverage of the area.Comment: In proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 201

Distributed approaches for coverage missions with multiple heterogeneous UAVs for coastal areas.

This Thesis focuses on a high-level framework proposal for heterogeneous aerial, fixed wing teams of robots, which operate in complex coastal areas. Recent advances in the computational capabilities of modern processors along with the decrement of small scale aerial platform manufacturing costs, have given researchers the opportunity to propose efficient and low-cost solutions to a wide variety of problems. Regarding marine sciences and more generally coastal or sea operations, the use of aerial robots brings forth a number of advantages, including information redundancy and operator safety. This Thesis initially deals with complex coastal decomposition in relation with a vehicles’ on-board sensor. This decomposition decreases the computational complexity of planning a flight path, while respecting various aerial or ground restrictions. The sensor-based area decomposition also facilitates a team-wide heterogeneous solution for any team of aerial vehicles. Then, it proposes a novel algorithmic approach of partitioning any given complex area, for an arbitrary number of Unmanned Aerial Vehicles (UAV). This partitioning schema, respects the relative flight autonomy capabilities of the robots, providing them a corresponding region of interest. In addition, a set of algorithms is proposed for obtaining coverage waypoint plans for those areas. These algorithms are designed to afford the non-holonomic nature of fixed-wing vehicles and the restrictions their dynamics impose. Moreover, this Thesis also proposes a variation of a well-known path tracking algorithm, in order to further reduce the flight error of waypoint following, by introducing intermediate waypoints and providing an autopilot parametrisation. Finally, a marine studies test case of buoy information extraction is presented, demonstrating in that manner the flexibility and modular nature of the proposed framework.Esta tesis se centra en la propuesta de un marco de alto nivel para equipos heterogéneos de robots de ala fija que operan en áreas costeras complejas. Los avances recientes en las capacidades computacionales de los procesadores modernos, junto con la disminución de los costes de fabricación de plataformas aéreas a pequeña escala, han brindado a los investigadores la oportunidad de proponer soluciones eficientes y de bajo coste para enfrentar un amplio abanico de cuestiones. Con respecto a las ciencias marinas y, en términos más generales, a las operaciones costeras o marítimas, el uso de robots aéreos conlleva una serie de ventajas, incluidas la redundancia de la información y la seguridad del operador. Esta tesis trata inicialmente con la descomposición de áreas costeras complejas en relación con el sensor a bordo de un vehículo. Esta descomposición disminuye la complejidad computacional de la planificación de una trayectoria de vuelo, al tiempo que respeta varias restricciones aéreas o terrestres. La descomposición del área basada en sensores también facilita una solución heterogénea para todo el equipo para cualquier equipo de vehículos aéreos. Luego, propone un novedoso enfoque algorítmico de partición de cualquier área compleja dada, para un número arbitrario de vehículos aéreos no tripulados (UAV). Este esquema de partición respeta las capacidades relativas de autonomía de vuelo de los robots, proporcionándoles una región de interés correspondiente. Además, se propone un conjunto de algoritmos para obtener planes de puntos de cobertura para esas áreas. Estos algoritmos están diseñados teniendo en cuenta la naturaleza no holonómica de los vehículos de ala fija y las restricciones que impone su dinámica. En ese sentido, esta Tesis también ofrece una variación de un algoritmo de seguimiento de rutas bien conocido, con el fin de reducir aún más el error de vuelo del siguiente punto de recorrido, introduciendo puntos intermedios y proporcionando una parametrización del piloto automático. Finalmente, se presenta un caso de prueba de estudios marinos de extracción de información de boyas, que demuestra de esa manera la flexibilidad y el carácter modular del marco propuesto

Simultaneous Deployment and Tracking Multi-Robot Strategies with Connectivity Maintenance

Multi robot teams composed by ground and aerial vehicles have gained attention during the last years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper we propose two Lloyd-based tracking strategies to allow the ground robots (agents) follow the aerial ones (targets), keeping the connectivity between the agents. The first strategy establishes density functions on the environment so that the targets acquire more importance than other zones, while the second one iteratively modifies the virtual limits of the working area depending on the positions of the targets. We consider the connectivity maintenance due to the fact that coverage tasks tend to spread the agents as much as possible, which is addressed by restricting their motions so that they keep the links of a Minimum Spanning Tree of the communication graph. We provide a thorough parametric study of the performance of the proposed strategies under several simulated scenarios. In addition, the methods are implemented and tested using realistic robotic simulation environments and real experiments

Multi robot cooperative area coverage, case study: spraying

Area coverage is a well-known problem in multi robotic systems, and it is a typical requirement in various real-world applications. A common and popular approach in the robotic community is to use explicit forms of communication for task allocation and coordination. These approaches are susceptible to the loss of communication signal, and costly with high computational complexity. There are very few approaches which are focused on implicit forms of communication. In these approaches, robots rely only on their local information for task allocation and coordination. In this paper, a cooperative strategy is proposed by which a team of robots perform spraying a large field. The focus of this paper is to achieve task allocation and coordination using only the robots' local information. Keywords: Multi Robotic System, Cooperative Behaviour, Coopera- tive Area Coverag

Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotic