Standard Particle Swarm Optimization on Source Seeking Using Mobile Robots

In this paper, we explore the implementation of standard particle swarm optimization (SPSO) on a swarm of physical mobile robots conducting a source seeking task. The signal source is electromagnetic, whose strength is non-differentiable at many points making most gradient based source seeking strategies ineffective in this scenario. We analyze the physical limitations of the robots and modify SPSO accordingly to make them compatible with each other. We also compare different SPSO topology models to determine the one best suited for our problem. Finally, we incorporate obstacle avoidance strategies into PSO, and compare the performance of original PSO, SPSO 2006 and SPSO 2011 in a complex environment with obstacles. Simulation results demonstrate the efficacy of implementing SPSO to robot source seeking problem. Moreover, it is shown that SPSO 2011 is not only superior as an optimization method, but also provides better performance in robotic implementation compared to SPSO 2006 and original PSO

Mobile robotic network deployment for intruder detection and tracking

This thesis investigates the problem of intruder detection and tracking using mobile robotic networks. In the first part of the thesis, we consider the problem of seeking an electromagnetic source using a team of robots that measure the local intensity of the emitted signal. We propose a planner for a team of robots based on Particle Swarm Optimization (PSO) which is a population based stochastic optimization technique. An equivalence is established between particles generated in the traditional PSO technique, and the mobile agents in the swarm. Since the positions of the robots are updated using the PSO algorithm, modifications are required to implement the PSO algorithm on real robots to incorporate collision avoidance strategies. The modifications necessary to implement PSO on mobile robots, and strategies to adapt to real environments are presented in this thesis. Our results are also validated on an experimental testbed. In the second part, we present a game theoretic framework for visibility-based target tracking in multi-robot teams. A team of observers (pursuers) and a team of targets (evaders) are present in an environment with obstacles. The objective of the team of observers is to track the team of targets for the maximum possible time. While the objective of the team of targets is to escape (break line-of-sight) in the minimum time. We decompose the problem into two layers. At the upper level, each pursuer is allocated to an evader through a minimum cost allocation strategy based on the risk of each evader, thereby, decomposing the agents into multiple single pursuer-single evader pairs. Two decentralized allocation strategies are proposed and implemented in this thesis. At the lower level, each pursuer computes its strategy based on the results of the single pursuer-single evader target-tracking problem. We initially address this problem in an environment containing a semi-infinite obstacle with one corner. The pursuer\u27s optimal tracking strategy is obtained regardless of the evader\u27s strategy using techniques from optimal control theory and differential games. Next, we extend the result to an environment containing multiple polygonal obstacles. We construct a pursuit field to provide a guiding vector for the pursuer which is a weighted sum of several component vectors. The performance of different combinations of component vectors is investigated. Finally, we extend our work to address the case when the obstacles are not polygonal, and the observers have constraints in motion

Kontrol Strategis pada Koperatif Multi Agen Pencarian Sumber Bergerak dengan Penghindaran Rintangan

Permasalahan eksplorasi dan penanggulangan bencana khususnya pencarian sumber bencana telah dilakukan oleh para peneliti, khususnya terkait permasalahan konsensus pada model multi-agen integrator tunggal. Permasalahan konsensus pada umumnya dikembangkan dengan (tanpa) perubahan topologi dengan beberapa kasus yang mungkin, seperti graf berarah dengan topologi tetap, graf berarah dengan perubahan topologi, dan graf tidak berarah dengan topologi tetap dan waktu tunda komunikasi. Pencarian sumber diam menggunakan konsensus gradien pada kooperatif multi-agen model integrator tunggal juga telah banyak dikembangkan dengan menggunakan kontrol formasi untuk menjaga perhitungan konsensus gradien tetap akurat. Selain itu, telah dikembangkan juga metode virtual artificial potential field (VAPF) yang digunakan untuk penghindaran rintangan diam dalam proses pencarian sumber bencana dimana posisi target diketahui. Disertasi ini mengusulkan solusi pencarian sumber bergerak berbasis kooperatif multi-agen dengan kontrol strategis, yaitu kombinasi kontrol kecepatan terdistribusi dan penghindaran rintangan. Dalam skema kontrol ini, suatu agen berkomunikasi dengan agen yang lain menggunakan topologi komunikasi untuk berkoordinasi dalam menemukan sumber. Sumber atau target pencarian dinyatakan dalam medan skalar. Dalam disertasi ini digunakan sumber bergerak secara linier atau sinusoidal dari titik awal ke titik akhir, dan sumber bergerak ini juga bisa mengembang dan menyempit. Keberadaan rintangan direpresentasikan dalam medan potensial buatan. Rintangan yang perlu dihindari oleh kooperatif multi-agen adalah rintangan diam dan bergerak. Agen dimodelkan dengan integrator ganda yang memiliki dinamika lebih kaya dibandingkan dengan model integrator tunggal. Kooperatif multi-agen integrator ganda dimodelkan dalam model state terintegrasi. Representasi ini menghasilkan informasi state semua agen secara simultan. Sinyal kontrol kooperatif multi-agen terdiri dari kontrol formasi, kontrol kecepatan terdistribusi, dan penghindaran rintangan. Kontrol formasi digunakan untuk memastikan bahwa agen tetap dalam formasi yang diinginkan selama manuver, agar perhitungan estimasi gradien dan konsensus gradien tetap akurat. Kontrol kecepatan terdistribusi merupakan kecepatan konsensus gradien yang dihasilkan dari estimasi gradien. Sedangkan metode penghindaran rintangan yang diusulkan dengan Modified Artificial Potential Field. Aturan kontrol strategis diusulkan untuk menjaga formasi, menentukan kecepatan masing-masing agen serta melacak sumber bergerak sambil menghindari rintangan bergerak. Perancangan kontrol strategis merupakan kombinasi kontrol kecepatan terdistribusi dan penghindaran rintangan, sedangkan kontrol formasi terintegrasi dalam kontrol kecepatan terdistribusi. Simulasi eksperimen pada disertasi ini menggunakan Object-Oriented Programming – MATLAB, yang meliputi perhitungan estimasi gradien, konsensus gradien, dan view manuver kooperatif multi-agen yang berinteraksi dengan sumber dan rintangan bergerak. Perhitungan estimasi gradien dan konsensus gradien merupakan perhitungan dari berbagi informasi posisi dan pengukuran intensitas sumber secara simultan antar satu agen dengan agen yang lain. Eksperimen yang dilakukan dalam disertasi ini merupakan kontrol strategis pencarian sumber bergerak linier dengan: a) penghindaran tiga rintangan diam, b) tiga rintangan diam dengan penyusutan formasi, dan c) dua rintangan diam-satu rintangan bergerak dengan penyusutan formasi. Dalam ketiga eksperimen tersebut, dibandingkan penghindaran rintangan menggunakan Modified Artificial Potential Field dan Virtual Artificial Potential Field. Hasil simulasi menunjukkan bahwa kooperatif multi-agen dapat mencari sumber bergerak dengan rintangan diam dan bergerak. Metode MAPF, kooperatif multi-agen dapat menemukan sumber dengan waktu pencarian yang lebih cepat dari VAPF, yakni 62,8 detik untuk eksperimen tiga rintangan diam dengan penyusutan formasi, dan 90 detik untuk eksperimen dua rintangan diam-satu rintangan bergerak dengan penyusutan formasi. Sebaliknya metode VAPF, kooperatif multi-agen dapat menemukan sumber dengan waktu pencarian lebih cepat dari MAPF, yakni 61,7 detik untuk eksperimen penghindaran tiga rintangan diam. Metode MAPF yang diusulkan lebih baik dibandingkan dengan metode VAPF, untuk eksperimen tiga rintangan diam dengan penyusutan formasi, dan eksperimen dua rintangan diam-satu rintangan bergerak dengan penyusutan formasi. ============================================================ The problem of exploration and disaster mitigation, especially the disaster sources seeking, has been carried out by researchers, especially regarding consensus issues in a single integrator multi-agent model. Consensus problems are generally developed with (without) a topology change with several possible cases, such as directed graphs with a fixed topology, directed graphs with switching topology, and undirected graphs with a fixed topology and communication delay. Stationary source seeking using gradient consensus in a cooperative multi-agent single integrator model has also been extensively developed using formation controls to keep gradient consensus calculations accurate. In addition, a virtual artificial potential field (VAPF) method has also been developed which is used to avoid stationary obstacles in the process of finding the source of a disaster where the position of the target is known. This dissertation proposes a cooperative multi-agent-based moving source seeking solution with strategic control, namely a combination of distributed speed control and obstacle avoidance. In this control scheme, an agent communicates with other agents using a communication topology to coordinate source seeking. The source seeking or target is expressed in a scalar field. In this dissertation a moving source is used linearly or sinusoidally from the starting point to the ending point, and this moving source can also expand and contract. The presence of obstacles is represented in an artificial potential field. The obstacles that multi-agent cooperatives need to avoid are stationary and moving obstacles. The agent is modeled with double integrator which have richer dynamics compared to the single integrator model. Double integrator cooperative multi-agent is modeled in integrated state model. This representation generates state information for all agents simultaneously. The cooperative multi-agent control signal consists of formation control, distributed speed control and obstacle avoidance. Formation control is used to ensure that agents remain in the desired formation during maneuvers, so that gradient estimation and gradient consensus calculations remain accurate. Distributed speed control is a consensus gradient speed resulting from gradient estimation. While the obstacle avoidance method proposed is the Modified Artificial Potential Field. Strategic control rules are proposed to maintain formations, determine each agent's speed as well as track moving resources while avoiding moving obstacles. Strategic control design is a combination of distributed speed control and obstacle avoidance, while formation control is integrated in distributed speed control. The experimental simulation in this dissertation uses Object-Oriented Programming – MATLAB, which includes calculations of gradient estimation, gradient consensus, and view of multi-agent cooperative maneuvers that interact with moving sources and obstacles. Calculation of gradient estimation and gradient consensus is a calculation of sharing position information and measuring source intensity simultaneously between one agent and another. Experiments carried out in this dissertation are strategic control of linear search for moving resources by: a) avoiding three stationary obstacles, b) three stationary obstacles with formation shrinkage, and c) two stationary obstacles-one moving obstacle with formation shrinkage. In these three experiments, obstacle avoidance was compared using the Modified Artificial Potential Field (MAPF) and the Virtual Artificial Potential Field (VAPF). The simulation results show that cooperative multi-agent can search for moving sources with stationary and moving obstacles. The MAPF method, multi-agent cooperatives can find resources with a faster search time than VAPF, namely 62.8 seconds for the three stationary obstacles experiment with formation shrinkage, and 90 seconds for the two stationary obstacles-one moving obstacle experiment with formation shrinkage. In contrast, the VAPF method, cooperative multi-agent can find sources with a search time that is faster than MAPF, which is 61.7 seconds for the three stationary obstacle avoidance experiment. The proposed MAPF method is better than the VAPF method, for the experiment of three stationary barriers with formation shrinkage, and the experiment of two stationary obstacles-one moving obstacle with formation shrinkage

Adaptive Navigation of Three-Dimensional Scalar Fields with Multiple UAVs

Adaptive Navigation (AN) control strategies allow an agent to autonomously alter its trajectory based on realtime measurements of its environment. Compared to conventional navigation methods, AN techniques can potentially reduce the time and energy needed to explore scalar characteristics of unknown and dynamic regions of interest (e.g., temperature, concentration level). Multiple Uncrewed Aerial Vehicle (UAV) approaches to AN can improve performance by exploiting synchronized spatially-dispersed measurements to generate realtime information regarding the structure of the local scalar field for use in navigation decisions. This dissertation presents initial results of a comprehensive program to develop, verify, and experimentally implement mission-level AN capabilities in three-dimensional (3D) space using Santa Clara University’s (SCU) unique multilayer control architecture for groups of vehicles. Using SCU’s flexible formation control system, this work builds upon prior 2D AN research and provides new contributions to 3D scalar field AN by a) demonstrating a wide range of 3D AN capabilities using a unified, multilayer control architecture, b) extending multivehicle 2D AN control primitives to navigation in 3D scalar fields, and c) introducing state-based sequencing of these primitive AN functions to execute 3D mission-level capabilities such as isosurface mapping and plume following. Functionality is verified using high-fidelity simulations of multivehicle drone clusters which account for vehicle dynamics, outdoor wind gust disturbances, position sensor inaccuracy, and scalar field sensor noise. This dissertation presents the multilayer architecture for multivehicle formation control, the 3D AN control primitives, the sequencing approaches for specific mission-level capabilities, and simulation results that demonstrate these functions

A cooperative advanced driver assistance and safety system for connected and automated vehicles

Konfliktsituationen mit mehreren Beteiligten sind für Fahrzeugführer und konventionelle Fahrerassistenz- und Sicherheitssysteme durch ihre hohe Komplexität schwer beherrschbar. So geschehen viele Unfälle auf den Straßen dieser Welt, die durch gemeinschaftlich abgestimmte Fahrmanöver verhindert oder in ihren Unfallfolgen gemindert werden könnten. Die vorliegende Arbeit adressiert dieses Potenzial und beschäftigt sich mit der Entwicklung und prototypischen Umsetzung eines fahrzeugübergreifenden kooperativen Fahrerassistenz- und Sicherheitssystems, welches mehrere Fahrzeuge über eine funkbasierte Kommunikation miteinander verbindet, sowie unfallfreie Lösungen berechnet und durchführt. In diesem Zusammenhang werden drei Forschungsfragen aufgestellt, die eine Definition von kooperativem Verhalten, eine Methode zur Koordination der anfallenden Aufgaben (Aufgabenkoordination) und eine Methode zur gemeinsamen Fahrmanöverplanung (Fahrmanöverkoordination) adressieren. Der Stand der Wissenschaft und Technik bezüglich der Forschungsfragen wird mithilfe einer systematischen Literaturstudie ermittelt, die für den Leser in einem Überblick dargestellt und hinsichtlich einer möglichen Beantwortung der Forschungsfragen ausgewertet wird. Es zeigt sich, dass die drei Forschungsfragen mit ihren Anforderungen bislang unbeantwortet sind. Zur Definition von kooperativem Verhalten werden Eigenschaften von diesem aufgezeigt, die in notwendige und hinreichende Bedingungen überführt werden. Mit der zusätzlichen Berücksichtigung von Reziprozität ergibt sich eine Definition von kooperativem Verhalten, welche durch die Steigerung des Gesamtnutzens die Unterscheidung zwischen unkooperativem Verhalten auf der einen Seite und rational-kooperativem, altruistisch-kooperativem bzw. egoistisch-kooperativem Verhalten auf der anderen Seite ermöglicht. Ein Vergleich mit den aus dem Stand der Technik bekannten Definitionen zeigt den Neuigkeitswert der entwickelten Definition. In ausgewählten Situationen wird die Definition in Simulationen angewandt.Critical situations involving multiple vehicles are rarely controlled by the associated drivers. This is one reason for the remaining number of accidents which could possibly be prevented or at least mitigated with jointly planned and conducted driving maneuvers. This potential is addressed in the dissertation at hand by developing a prototypical cooperative driver assistance and safety system coordinating multiple vehicles cooperatively using vehicle-to-vehicle-communication. In this context, three research questions reflect challenges on the road towards such a system. The research questions deal with defining a cooperative behavior, creating a method allowing to allocate coordinative tasks (task coordination), and generating a method enabling to plan joint cooperative maneuvers (maneuver coordination). Regarding the proposed research questions, a systematic literature review reveals the state-of-the-art which is first presented in an overview and afterwards used to derive open issues. The result is that the three research questions remain relevant and unanswered. In order to define cooperative behavior, properties are identified and categorized in sufficient and necessary conditions. An additional consideration of reciprocity enables the derivation of a definition of cooperative behavior which aims to increase the total utility. Cooperative behavior may further be separated into rational-cooperative, altruistic-cooperative, and egoistic-cooperative behavior. A comparison with known definitions of the state-of-the-art demonstrates the innovation of the novel definition, which is applied in chosen situations