Multi-agent Persistent Surveillance with Time-interval Constraints Using Mixed Integer Linear Programming

학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2014. 2. 김현진.In the past years, cooperative operation of multiple robots has attracted considerable research interest for coverage and search of broad and complex areas. Unlike the complete coverage problem, in the basic persistent surveillance problem each location in the environment must be visited repeatedly while minimizing the time-interval between any two visits to the same location. In this paper, we propose a cooperative path planning algorithm for an efficient persistent surveillance operation of multiple heterogeneous agents using mixed integer linear programming. Since we specially consider a grid environment with different priories (time interval constraints), agents must visit the region at least once within the specific time interval constraint. The cost function is the maximum risk minimization. Also, we consider a protocol for cooperative movement of heterogeneous agents. The objectives of the proposed algorithm are: persistent surveillance operation with time interval constraints, obstacle avoidance, and collision avoidance among multiple agents. Simulation results conrm that a cell is visited at least once within its time interval constraints.Table of Contents List of Tables List of Figures Chapter 1 Introduction 1.1 Previous Works 1.2 Contributions 1.3 Thesis Overviews 2 Setup for Persistent Surveillance 2.1 Heterogeneous Agents 2.2 Environment Setting 3 MILP Formulations 3.1 Introduction to MILP 3.2 Objective Function 3.3 Location Constraints 3.4 Movement Constraints 3.5 Capability Constraints 3.6 Time-interval Constraints 4 Protocol for Cooperative Movement 4.1 Denition of Safe Zone 4.2 Task Assignment 4.3 Decision Making Behaviour Model 4.4 Overall Algorithm 5 Simulation 5.1 Simulation Setting 5.2 Simulation Results 6 ConclusionsMaste

Honeycomb map: a bioinspired topological map for indoor search and rescue unmanned aerial vehicles

The use of robots to map disaster-stricken environments can prevent rescuers from being harmed when exploring an unknown space. In addition, mapping a multi-robot environment can help these teams plan their actions with prior knowledge. The present work proposes the use of multiple unmanned aerial vehicles (UAVs) in the construction of a topological map inspired by the way that bees build their hives. A UAV can map a honeycomb only if it is adjacent to a known one. Different metrics to choose the honeycomb to be explored were applied. At the same time, as UAVs scan honeycomb adjacencies, RGB-D and thermal sensors capture other data types, and then generate a 3D view of the space and images of spaces where there may be fire spots, respectively. Simulations in different environments showed that the choice of metric and variation in the number of UAVs influence the number of performed displacements in the environment, consequently affecting exploration time and energy use.info:eu-repo/semantics/publishedVersio

A Collaborative Visual Localization Scheme for a Low-Cost Heterogeneous Robotic Team with Non-Overlapping Perspectives

This paper presents and evaluates a relative localization scheme for a heterogeneous team of low-cost mobile robots. An error-state, complementary Kalman Filter was developed to fuse analytically-derived uncertainty of stereoscopic pose measurements of an aerial robot, made by a ground robot, with the inertial/visual proprioceptive measurements of both robots. Results show that the sources of error, image quantization, asynchronous sensors, and a non-stationary bias, were sufficiently modeled to estimate the pose of the aerial robot. In both simulation and experiments, we demonstrate the proposed methodology with a heterogeneous robot team, consisting of a UAV and a UGV tasked with collaboratively localizing themselves while avoiding obstacles in an unknown environment. The team is able to identify a goal location and obstacles in the environment and plan a path for the UGV to the goal location. The results demonstrate localization accuracies of 2cm to 4cm, on average, while the robots operate at a distance from each-other between 1m and 4m

Algorithms for multi-robot systems on the cooperative exploration & last-mile delivery problems

La aparición de los vehículos aéreos no tripulados (UAVs) y de los vehículos terrestres no tripulados (UGVs) ha llevado a la comunidad científica a enfrentarse a problemas ideando paradigmas de cooperación con UGVs y UAVs. Sin embargo, no suele ser trivial determinar si la cooperación entre UGVs y UAVs es adecuada para un determinado problema. Por esta razón, en esta tesis, investigamos un paradigma particular de cooperación UGV-UAV en dos problemas de la literatura, y proponemos un controlador autónomo para probarlo en escenarios simulados. Primero, formulamos un problema particular de exploración cooperativa que consiste en alcanzar un conjunto de puntos de destino en un área de exploración a gran escala. Este problema define al UGV como una estación de carga móvil para transportar el UAV a través de diferentes lugares desde donde el UAV puede alcanzar los puntos de destino. Por consiguiente, proponemos el algoritmo TERRA para resolverlo. Este algoritmo se destaca por dividir el problema de exploración en cinco subproblemas, en los que cada subproblema se resuelve en una etapa particular del algoritmo. Debido a la explosión de la entrega de paquetes en las empresas de comercio electrónico, formulamos también una generalización del conocido problema de la entrega en la última milla. En este caso, el UGV actúa como una estación de carga móvil que transporta a los paquetes y a los UAVs, y estos se encargan de entregarlos. De esta manera, seguimos la estrategia de división descrita por TERRA, y proponemos el algoritmo COURIER. Este algoritmo replica las cuatro primeras etapas de TERRA, pero construye una nueva quinta etapa para producir un plan de tareas que resuelva el problema. Para evaluar el paradigma de cooperación UGV-UAV en escenarios simulados, proponemos el controlador autónomo ARIES. Este controlador sigue un enfoque jerárquico descentralizado de líder-seguidor para integrar cualquier paradigma de cooperación de manera distribuida. Ambos algoritmos han sido caracterizados para identificar los aspectos relevantes del paradigma de cooperación en los problemas relacionados. Además, ambos demuestran un gran rendimiento del paradigma de cooperación en tales problemas, y al igual que el controlador autónomo, revelan un gran potencial para futuras aplicaciones reales.The emergence of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has conducted the research community to face historical complex problems by devising UGV-UAV cooperation paradigms. However, it is usually not a trivial task to determine whether or not a UGV-UAV cooperation is suitable for a particular problem. For this reason, in this thesis, we investigate a particular UGV-UAV cooperation paradigm over two problems in the literature, and we propose an autonomous controller to test it on simulated scenarios. Driven by the planetary exploration, we formulate a particular cooperative exploration problem consisting of reaching a set of target points in a large-scale exploration area. This problem defines the UGV as a moving charging station to carry the UAV through different locations from where the UAV can reach the target points. Consequently, we propose the cooperaTive ExploRation Routing Algorithm (TERRA) to solve it. This algorithm stands out for splitting up the exploration problem into five sub-problems, in which each sub-problem is solved in a particular stage of the algorithm. In the same way, driven by the explosion of parcels delivery in e-commerce companies, we formulate a generalization of the well-known last-mile delivery problem. This generalization defines the same UGV’s and UAV’s rol as the exploration problem. That is, the UGV acts as a moving charging station which carries the parcels along several UAVs to deliver them. In this way, we follow the split strategy depicted by TERRA to propose the COoperative Unmanned deliveRIEs planning algoRithm (COURIER). This algorithm replicates the first four TERRA’s stages, but it builds a new fifth stage to produce a task plan solving the problem. In order to evaluate the UGV-UAV cooperation paradigm on simulated scenarios, we propose the Autonomous coopeRatIve Execution System (ARIES). This controller follows a hierarchical decentralized leader-follower approach to integrate any cooperation paradigm in a distributed manner. Both algorithms have been characterized to identify the relevant aspects of the cooperation paradigm in the related problems. Also, both of them demonstrate a great performance of the cooperation paradigm in such problems, and as well as the autonomous controller, reveal a great potential for future real applications

Coordination of Cooperative Multi-Robot Teams

This thesis is about cooperation of multiple robots that have a common task they should fulfill, i.e., how multi-robot systems behave in cooperative scenarios. Cooperation is a very important aspect in robotics, because multiple robots can solve a task more quickly or efficiently in many situations. Specific points of interest are, how the effectiveness of the group of robots completing a task can be improved and how the amount of communication and computational requirements can be reduced. The importance of this topic lies in applications like search and rescue scenarios, where time can be a critical factor and a certain robustness and reliability are required. Further the communication can be limited by various factors and operating (multiple) robots can be a highly complicated task. A typical search and rescue mission as considered in this thesis begins with the deployment of the robot team in an unknown or partly known environment. The team can be heterogeneous in the sense that it consists of pairs of air and ground robots that assist each other. The air vehicle – abbreviated as UAV – stays within vision range of the ground vehicle or UGV. Therefrom, it provides sensing information with a camera or similar sensor that might not be available to the UGV due to distance, perspective or occlusion. A new approach to fully use the available movement range is presented and analyzed theoretically and in simulations. The UAV moves according to a dynamic coverage algorithm which is combined with a tracking controller to guarantee the visibility limitation is kept. Since the environment is at least partly unknown, an exploration method is necessary to gather information about the situation and possible targets or areas of interest. Exploring the unknown regions in a short amount of time is solved by approaching points on the frontier between known and unknown territory. To this end, a basic approach for single robot exploration that uses the traveling salesman problem is extended to multirobot exploration. The coordination, which is a central aspect of the cooperative exploration process, is realized with a pairwise optimization procedure. This new algorithm uses minimum spanning trees for cost estimation and is inspired by one of the many multi-robot coordination methods from the related literature. Again, theoretical and simulated as well as statistical analysis are used as methods to evaluate the approach. After the exploration is complete, a map of the environment with possible regions of higher importance is known by the robot team. To stay useful and ready for any further events, the robots now switch to a monitoring state where they spread out to cover the area in an optimal manner. The optimality is measured with a criterion that can be derived into a distributed control law. This leads to splitting of the robots into areas of Voronoi cells where each robot has a maximum distance to other robots and can sense any events within its assigned cell. A new variant of these Voronoi cells is introduced. They are limited by visibility and depend on a delta-contraction of the environment, which leads to automatic collision avoidance. The combination of these two aspects leads to a coverage control algorithm that works in nonconvex environments and has advantageous properties compared to related work

Automation and Control

Advances in automation and control today cover many areas of technology where human input is minimized. This book discusses numerous types and applications of automation and control. Chapters address topics such as building information modeling (BIM)–based automated code compliance checking (ACCC), control algorithms useful for military operations and video games, rescue competitions using unmanned aerial-ground robots, and stochastic control systems

Coverage Path Planning for a Moving Vehicle

A simple coverage plan called a Conformal Lawn Mower plan is demonstrated. This plan enables a UAV to fully cover the route ahead of a moving ground vehicle. The plan requires only limited knowledge of the ground vehicle's future path. For a class of curvature-constrained ground vehicle paths, the proposed plan requires a UAV velocity that is no more than twice the velocity required to cover the optimal plan. Necessary and sufficient UAV velocities, relative to the ground vehicle velocity, required to successfully cover any path in the curvature restricted set are established. In simulation, the proposed plan is validated, showing that the required velocity to provide coverage is strongly related to the curvature of the ground vehicle's path. The results also illustrate the relationship between mapping requirements and the relative velocities of the UAV and ground vehicle. Next, I investigate the challenges involved in providing timely mapping information to a moving ground vehicle where the path of that vehicle is not known in advance. I establish necessary and sufficient UAV velocities, relative to the ground vehicle velocity, required to successfully cover any path the ground vehicle may follow. Finally, I consider a reduced problem for sensor coverage ahead of a moving ground vehicle. Given the ground vehicle route, the UAV planner calculates the regions that must be covered and the time by which each must be covered. The UAV planning problem takes the form of an Orienteering Problem with Time Windows (OPTW). The problem is cast the problem as a Mixed Integer Linear Program (MILP) to find a UAV path that maximizes the area covered within the time constraints dictated by the moving ground vehicle. To improve scalability of the proposed solution, I prove that the optimization can be partitioned into a set of smaller problems, each of which may be solved independently without loss of overall solution optimality. This divide and conquer strategy allows faster solution times, and also provides higher-quality solutions when given a fixed time budget for solving the MILP. We also demonstrate a method of limited loss partitioning, which can perform a trade-off between improved solution time and a bounded objective loss

Dynamic virtual reality user interface for teleoperation of heterogeneous robot teams

This research investigates the possibility to improve current teleoperation control for heterogeneous robot teams using modern Human-Computer Interaction (HCI) techniques such as Virtual Reality. It proposes a dynamic teleoperation Virtual Reality User Interface (VRUI) framework to improve the current approach to teleoperating heterogeneous robot teams

A review on multi-robot systems categorised by application domain

Literature reviews on Multi-Robot Systems (MRS) typically focus on fundamental technical aspects, like coordination and communication, that need to be considered in order to coordinate a team of robots to perform a given task effectively and efficiently. Other reviews only consider works that aim to address a specific problem or one particular application of MRS. In contrast, this paper presents a survey of recent research works on MRS and categorises them according to their application domain. Furthermore, this paper compiles a number of seminal review works that have proposed specific taxonomies in classifying fundamental concepts, such as coordination, architecture and communication, in the field of MRS.peer-reviewe