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作者： Malencia, Matthew University of Pennsylvania

学位级别：Ph.D., Doctor of Philosophy

multi robot systems are growing rapidly, expanding beyond factories and into our daily lives. Because these systems exist within social contexts, it is crucial that their decisions fairly treat those being served. Therefore, this thesis leverages principles of fairness to create definitions and measures that are relevant to the application of multi robot systems in societal settings. These definitions are used to investigate the impact of existing approaches and to develop new methods. A core principle of fairness examined in this thesis is perspective, which considers whose outcomes are being compared. We start with a narrow perspective of fairness, comparing individuals' outcomes. We expand this perspective throughout the thesis to study fairness between populations. Our presented methods mirror this progression: we start with algorithms that make decisions based on individual attributes and end with small robot teams that serve large populations. We demonstrate the use and impact of our methods in applications like emergency delivery and disaster response.

关键词： multi robot systems Disaster response Alteroceptive cultures Fairness concept

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Towards the Achievement of Path Planning with multi-robot systems in Dynamic Environments

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JOURNAL OF INTELLIGENT & robotIC systems 2022年第1期104卷 1-18页

作者： Kyprianou, G. Doitsidis, L. Chatzichristofis, S. A. Neapolis Univ Pafos Intelligent Syst Lab Dept Comp Sci Paphos Cyprus Tech Univ Crete Sch Prod Engn & Management Khania Greece

Recent advances in technology lead to the use of robotic systems as part of the modern working environment. Single and multiple robotic systems work closely with humans to accomplish desired tasks, and the recent advancements have made the usage of multi-robot teams more appealing. One critical problem in utilizing the robot's full potential is the Path planning problem and, while in the case of a single's robot, path planning has been extensively investigated, in the case of multiple robotic systems (MRS), especially in dynamic changing environments, there are significant open challenges. Based on the statement mentioned above, a detailed survey has been conducted to highlight these challenges and identify potential solutions. In addition, the beneficial use of MRS is presented, as opposed to single robotic systems through the literature, and already-achievable industry-related results are provided. It is concluded that the practical application of path planning in dynamic environments using MRS is still a field of research and development, requiring the community to engage more with practical applications.

关键词： Algorithms Artificial intelligence Dynamic environment Industrial automation multi robot systems Path planning

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A design optimization technique for multi-robot systems 55

A design optimization technique for multi-robot systems

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55th AIAA Aerospace Sciences Meeting

作者： Durand, Jean-Guillaume Burgaud, Frédéric Cooksey, K.D. Mavris, Dimitri N. Georgia Institute of Technology AtlantaGA30332-0150 United States School of Aerospace Engineering 270 Ferst Dr Mail Stop 0150 United States Aerospace Systems Design Laboratory 275 Ferst Drive #3 AtlantaGA30332 United States Aerospace Systems Design Laboratory School of Aerospace Engineering 270 Ferst Dr Mail Stop 0150 United States

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

Despite being more flexible, robust, and scalable than single robot solutions, multi-robot systems suffer from a lack of democratization. Most applications are found in academia or rare avant-gardist military projects with very few, if none, commercial implementations. This is due in part to the complex system of systems design process requiring the optimization of not only the group architecture, but also the individual agents, for the group operation. Such an intricate procedure, as well as the lack of link between the microscopic level and the macroscopic level of the system, leads to suboptimal designs. Focused on micro unmanned aerial vehicles, this paper proposes a novel bi-lebel optimization technique which differs from the classical sequential approach presently utilized by the community. The results of this global optimization scheme applied to a simple example show that performance improvements up to thirty percent can be achieved on designs. Moreover, the optimization step is shown to be not more computationally expensive than the current paradigm. © 2017 by Jean-Guillaume Durand, Frédéric Burgaud, K. D. Cooksey, Dimitri N. Mavris.

关键词： multi robot systems Aerial robots Unmanned Aerial Vehicle Swarm robotics Optimization Algorithm Supply Chain Management Genetic Algorithm Space Exploration Aerodynamics Metaheuristic Approach

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Offloading Monocular Visual Odometry with Edge Computing: Optimizing Image Quality in multi-robot systems 19

Offloading Monocular Visual Odometry with Edge Computing: Op...

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Proceedings of the 2019 5th International Conference on systems, Control and Communications

作者： Li Qingqing Jorge Pena Queralta Tuan Nguyen Gia Tomi Westerlund University of Turku Turku Finland

ISBN: (纸本)9781450372640

Fleets of autonomous mobile robots are becoming ubiquitous in industrial environments such as logistic warehouses. This ubiquity has led in the Internet of Things field towards more distributed network architectures, which have crystallized under the rising edge and fog computing paradigms. In this paper, we propose the combination of an edge computing approach with computational offloading for mobile robot navigation. As smaller and relatively simpler robots become more capable, their penetration in different domains rises. These large multi-robot systems are often characterized by constrained computational and sensing resources. An efficient computational offloading scheme has the potential to bring multiple operational enhancements. However, with the most cost-effective autonomous navigation method being visual-inertial odometry, streaming high-quality images can induce latency increments with a consequent negative impact on operational performance. In this paper, we analyze the impact that image quality and compression have on the state-of-the-art on visual inertial odometry. Our results indicate that over one order of magnitude in image size and network bandwidth can be reduced without compromising the accuracy of the odometry methods even in challenging environments. This opens the door to further optimization by dynamically assessing the trade-off between image quality, network load, latency and performance of the visual-inertial odometry and localization accuracy.

关键词： multi robot systems Internet of robots Visual-Inertial Odometry Image Compression Edge Computing Internet of Vehicles Computational Offloading Monocular Visual Odometry Visual Odometry

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Dual-layer multi-robot path planning in narrow-lane environments under specific traffic policies

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INTELLIGENT SERVICE robotICS 2022年第4期15卷 537-555页

作者： Huo, Jiaxi Zheng, Ronghao Zhang, Senlin Liu, Meiqin Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China

Collision-free path planning is indispensable for the multi-robot system. Many existing multi-robot path planning algorithms may no longer work properly in the narrow-lane environment. We propose in this paper a dual-layer algorithm to deal with the multi-robot path planning problem in the narrow-lane environment. In the first layer, the integer programming technique primarily based on distance metrics balances the optimality of the generated collision-free paths and the computation time of the algorithm. In the second layer, fast feasible heuristics are applied to make sure the solvability of the proposed integer programming approach in the first layer. In the dual-layer algorithm, specific traffic policies for each narrow lane are implemented to generate a collision-free path for every robot while maintaining the narrow lane free, besides the collision avoidance approach at the robotic level. With this, inter-robot collision in the narrow lane is avoided, and the algorithm's efficiency in producing collision-free paths increases. Simulations have been launched considerably based on the proposed assessment metrics. According to the extensive simulation data, our algorithm suggests a higher overall performance in the narrow-lane environment when in contrast with the present optimal, sub-optimal, and polynomial-complexity algorithms.

关键词： multi robot systems Path planning Moving robots Industrial automation Optimization algorithms

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Buzz A Programming Language for robot Swarms

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IEEE SOFTWARE 2016年第4期33卷 97-100页

作者： Pinciroli, Carlo Beltrame, Giovanni Ecole Polytech MIST Making Innovat Space Technol Lab Montreal PQ Canada Ecole Polytech Dept Comp Engn Montreal PQ Canada MIST Making Innovat Space Technol Lab Montreal PQ Canada

From drones to self-driving cars, robot swarms are becoming pervasive and are used in many kinds of applications. However, common "swarm libraries" for software development do not yet exist, and reusing code is difficult owing to the lack of swarm-centric development platforms. Buzz, a programming language for heterogeneous robot swarms, aims to address these problems.

关键词： Control Engineering Computing multi robot systems Programming Languages robot Programming Swarm Intelligence Buzz Programming Language robot Swarm robot Kinematics Service robots Particle Swarm Optimization robot Sensing systems Computer Languages Biological System Modeling Buzz robot Swarms robotics Software Engineering Software Development Programming Languages

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Non-homogeneous multi-robot Collaboration for Environment Mapping and Inference 4

Non-homogeneous Multi-robot Collaboration for Environment Ma...

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4th International Conference on robotics, Control and Automation Engineering (RCAE) / 4th International Conference on Advanced Mechanical and Electrical Engineering (AMEE)

作者： Hensley, Crockett Patel, Parth Koduru, Charles Tanveer, M. Hassan Kennesaw State Univ Dept Robot & Mechatron Engn Marietta GA 30060 USA

ISBN: (纸本)9781665427302

multi-robot collaboration is the subject of a great deal of research currently. This interest within the field of robotics is prominent because multiple robots can often complete complex tasks faster and more efficiently than a single robot. The majority of the research being done today is related to homogeneous robotic communities, wherein each robot has the same equipment and limitations. The scenario becomes more challenging by introducing non-homogenous teams of robots. In this paper, we explore a non-homogeneous robotic community where one robot (acting as master) is designated to map an area while a different robot (acting as slave) infers from that map. Such a system is demonstrated to be reliable within a small and primarily static environment using two mobile robots equipped with RGB-D cameras and planar LiDAR sensors. This type of role assignment allows for more specialized equipment for both robots as well as greater optimization of the robots' tasks.

关键词： multi robot systems RGB-D cameras Lidar Sensor

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Incremental evolution of stigmergy-based multi robot controllers through utility functions

Incremental evolution of stigmergy-based multi robot control...

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11th International Conference on Knowledge-Based Intelligent Informational and Engineering systems/17th Italian Workshop on Neural Networks

作者： Caamano, P. Becerra, J. A. Duro, R. J. Bellas, F. Integrated Group for Engineering Research Universidade da Coruña Spain

ISBN: (纸本)9783540748267

This paper deals with the problem of jointly designing the behaviors of a group of robots so as to produce a particular desired collaborative behavior in stigmergy-based settings. In this line, the approach followed has its roots on traditional evolutionary behavior based robotics techniques, but instead of trying to evolve the whole controller for a particular complex behavior in one step, an incremental approach is used by combining the results from different evolutionary/learning processes in different settings for the construction of a complete controller architecture. The key aspects when trying to generalize the process of obtaining the controllers from single robots to multi robot systems are discussed in the framework of a set of simple collaborative tasks, focusing the discussion on the utility functions that guide the evolution.

关键词： multi robot systems collaborative behaviors evolutionary algorithms utility functions neural networks

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Behavior Based multi robot Formations with Active Obstacle Avoidance based on Switching Control Strategy

Behavior Based Multi Robot Formations with Active Obstacle A...

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International Conference on Materials Science and Information Technology (MSIT 2011)

作者： Chetty, Kuppan R. M. Singaperumal, M. Nagarajan, T. Monash Univ Sch Engn Sunway Campus Bandar Sunway Malaysia Indian Inst Technol Dept Engn Mech Madras Tamil Nadu India

ISBN: (纸本)9783037853191

This paper considers the problem of formation control and obstacle avoidance for a group of non-holonomic mobile robots in a leader referenced model based on reactive switching control strategy. Three important issues related to the multi robot formation namely distributed formation control framework, dynamic role switching algorithm and real time implementations are investigated. The switching control strategy combines together formation planning, navigation and active obstacle avoidance in a layered control framework composed of functional behaviors based on the relative motion states of the robots employed in the group. Dynamic role switching mechanism incorporated in this work to tackles the problem of obstacle avoidance in the follower path. The proposed approach is validated through laboratory experiments using commercially available robot research platforms and the results obtained are discussed.

关键词： multi robot systems Behavior Based Control Non holonomic systems Switching Control Strategy State based approach Formation Control

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An Intelligent Approach for a Two-robot Team to Perform a Cooperative Task

An Intelligent Approach for a Two-robot Team to Perform a Co...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Sun, Yufeng Barth, Andrew Ma, Ou Univ Cincinnati Dept Aerosp Engn & Engn Mech Cincinnati OH 45221 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Complex future space missions will increasingly rely on human-robot or robot-robot collaboration, which requires the robots to have intelligent capabilities. This paper introduces a decentralized approach of two independent robots to cooperatively accomplish a common task. The task of the robot team is to transport a payload to outside a room through a narrow door. There is no pre-programmed motion trajectory for the two robots to follow and no communication between the robots which means each robot does not know how the other robot will react at any instant. The only information available to each robot is its own position and the pose of the payload. Genetic Fuzzy System (GFS) is employed to train the controllers of individual robots. The kinematics and dynamics models are considered and simulated in MATLAB environment, which have shown that the proposed intelligent control method can be trained to control the two individual robots to successfully achieve their common goal. To demonstrate the effectiveness of this approach, the robot team is trained with a set of scenarios and then verified with an extensive test set.

关键词： Mobile robots Genetic Fuzzy systems Space Missions MATLAB Fuzzy Control System Astronaut multi robot systems Particle Swarm Optimization Path Planning Satellites

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