Simultaneous deployment and tracking multi-robot strategies with connectivity maintenance

Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few 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) to 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

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

Cooperative Swarm Optimisation of Unmanned Surface Vehicles

Edited version embargoed 10 07.01.2020 Full version: Access restricted permanently due to 3rd party copyright restrictions. Restriction set on 11/04/2019 by AS, Doctoral CollegeWith growing advances in technology and everyday dependence on oceans for resources, the role of unmanned surface vehicles (USVs) has increased many fold. Extensive operations of USVs having naval, civil and scientific applications are currently being undertaken in various complex marine environments and demands are being placed on them to increase their autonomy and adaptability. A key requirement for the autonomous operation of USVs is to possess a multi-vehicle framework where they can operate as a fleet of vehicles in a practical marine environment with multiple advantages such as surveying of wider areas in less time. From the literature, it is evident that a huge number of studies has been conducted in the area of single USV path planning, guidance and control whilst very few studies have been conducted to understand the implications of the multi vehicle approaches to USVs. This present PhD thesis integrates the modules of efficient optimal path planning, robust path following guidance and cooperative swarm aggregation approach towards development of a new hybrid framework for cooperative navigation of swarm of USVs to enable optimal and autonomous operation in a maritime environment. Initially, an effective and novel optimal path planning approach based on the A* algorithm has been designed taking into account the constraint of a safety distance from the obstacles to avoid the collisions in scenarios of moving obstacles and sea surface currents. This approach is then integrated with a novel virtual target path following guidance module developed for USVs where the reference trajectory from the path planner is fed into the guidance system. The novelty of the current work relies on combining the above mentioned integrated path following guidance system with decentralised swarm aggregation behaviour by means of simple potential based attraction and repulsion functions to maintain the centroid of the swarm of USVs and thereby guiding the swarm of USVs onto a reference path. Finally, an optimal and hybrid framework for cooperative navigation and guidance of fleet of USVs, implementable in practical maritime environments and effective for practical applications at sea is presented.Commonwealth Scholarship Commissio

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics

Swarm Robotic Systems with Minimal Information Processing

This thesis is concerned with the design and analysis of behaviors in swarm robotic systems using minimal information acquisition and processing. The motivation for this work is to contribute in paving the way for the implementation of swarm robotic systems at physically small scales, which will open up new application domains for their operation. At these scales, the space and energy available for the integration of sensors and computational hardware within the individual robots is at a premium. As a result, trade-offs in performance can be justified if a task can be achieved in a more parsimonious way. A framework is developed whereby meaningful collective behaviors in swarms of robots can be shown to emerge without the robots, in principle, possessing any run-time memory or performing any arithmetic computations. This is achieved by the robots having only discrete-valued sensors, and purely reactive controllers. Black-box search methods are used to automatically synthesize these controllers for desired collective behaviors. This framework is successfully applied to two canonical tasks in swarm robotics: self-organized aggregation of robots, and self-organized clustering of objects by robots. In the case of aggregation, the robots are equipped with one binary sensor, which informs them whether or not there is another robot in their line of sight. This makes the structure of the robots’ controller simple enough that its entire space can be systematically searched to locate the optimal controller (within a finite resolution). In the case of object clustering, the robots’ sensor is extended to have three states, distinguishing between robots, objects, and the background. This still requires no run-time memory or arithmetic computations on the part of the robots. It is statistically shown that the extension of the sensor to have three states leads to a better performance as compared to the cases where the sensor is binary, and cannot distinguish between robots and objects, or robots and the background

Técnicas de pastoreo multi robot

El trabajo se va a centrar en un sistema multi-robot con un objetivo particular: poder controlar y llevar a un punto objetivo un grupo de animales (ovejas, vacas…). El control se realiza en base a un algoritmo de un artículo científico y se realizan simulaciones en las que existen dos tipos de robots: los robots cooperativos (dogs) y los robots no cooperativos (sheeps). En estos últimos se introducirán una serie de movimientos para simular el comportamiento de los rebaños. El trabajo explica paso a paso cómo ha ido construyéndose el control. También las diversas simulaciones que se realizan para verificar el comportamiento del algoritmo y sus resultados. <br /

Decentralized receding horizon control of cooperative vehicles with communication delays

This thesis investigates the decentralized receding horizon control (DRHC) for a network of cooperative vehicles where each vehicle in the group plans its future trajectory over a finite prediction horizon time. The vehicles exchange their predicted paths with the neighbouring vehicles through a communication channel in order to maintain the cooperation objectives. In this framework, more frequent communication provides improved performance and stability properties. The main focus of this thesis is on situations where large inter-vehicle communication delays are present. Such large delays may occur due to fault conditions with the communication devices or limited communication bandwidth. Large communication delays can potentially lead to poor performance, unsafe behaviour and even instability for the existing DRHC methods. The main objective of this thesis is to develop new DRHC methods that provide improved performance and stability properties in the presence of large communication delays. Fault conditions are defined and diagnosis algorithms are developed for situations with large communication delays. A fault tolerant DRHC architecture is then proposed which is capable of effectively using the delayed information. The main idea with the proposed approach is to estimate the path of the neighbouring faulty vehicles, when they are unavailable due to large delays, by adding extra decision variables to the cost function. It is demonstrated that this approach can result in significant improvements in performance and stability. Furthermore, the concept of the tube DRHC is proposed to provide the safety of the fleet against collisions during faulty conditions. In this approach, a tube shaped trajectory is assumed in the region around the delayed trajectory of the faulty vehicle instead of a line shaped trajectory. The neighbouring vehicles calculate the tube and are not allowed to enter that region. Feasibility, stability, and performance of the proposed fault tolerant DRHC are also investigated. Finally, a bandwidth allocation algorithm is proposed in order to optimize the communication periods so that the overall teaming performance is optimized. Together, these results form a new and effective framework for decentralized receding horizon control with communication faults and large communication delays

Planification de trajectoire et contrôle d'un système collaboratif : Application à un drone trirotor

This thesis is dedicated to the creation of a complete framework, from high-level to low-level, of trajectory generation for a group of independent dynamical systems. This framework, based for the trajectory generation, on the resolution of Burgers equation, is applied to a novel model of trirotor UAV and uses the flatness of the two levels of dynamical systems.The first part of this thesis is dedicated to the generation of trajectories. Formal solutions to the heat equation are created using the differential flatness of this equation. These solutions are transformed into solutions to Burgers' equation through Hopf-Cole transformation to match the desired formations. They are optimized to match specific requirements. Several examples of trajectories are given.The second part is dedicated to the autonomous trajectory tracking by a trirotor UAV. This UAV is totally actuated and a nonlinear closed-loop controller is suggested. This controller is tested on the ground and in flight by tracking, rolling or flying, a trajectory. A model is presented and a control approach is suggested to transport a pendulum load.L'objet de cette thèse est de proposer un cadre complet, du haut niveau au bas niveau, de génération de trajectoires pour un groupe de systèmes dynamiques indépendants. Ce cadre, basé sur la résolution de l'équation de Burgers pour la génération de trajectoires, est appliqué à un modèle original de drone trirotor et utilise la platitude des deux systèmes différentiels considérés. La première partie du manuscrit est consacrée à la génération de trajectoires. Celle-ci est effectuée en créant formellement, par le biais de la platitude du système considéré, des solutions à l'équation de la chaleur. Ces solutions sont transformées en solution de l'équation de Burgers par la transformation de Hopf-Cole pour correspondre aux formations voulues. Elles sont optimisées pour répondre à des contraintes spécifiques. Plusieurs exemples de trajectoires sont donnés.La deuxième partie est consacrée au suivi autonome de trajectoire par un drone trirotor. Ce drone est totalement actionné et un contrôleur en boucle fermée non-linéaire est proposé. Celui-ci est testé en suivant, en roulant, des trajectoires au sol et en vol. Un modèle est présenté et une démarche pour le contrôle est proposée pour transporter une charge pendulaire