Decentralized Method for Sub-swarm Deployment and Rejoining

As part of swarm search and service (SSS) missions, robots are tasked with servicing jobs as they are sensed. This requires small sub-swarm teams to leave the swarm for a specified amount of time to service the jobs. In doing so, fewer robots are required to change motion than if the whole swarm were diverted, thereby minimizing the job’s overall effect on the swarm’s main goal. We explore the problem of removing the required number of robots from the swarm, while maintaining overall swarm connectivity. By preserving connectivity, robots are able to successfully rejoin the swarm upon completion of their assigned job. These robots are then made available for reallocation. We propose a decentralized and asynchronous method for breaking off sub-swarm groups and rejoining them with the main swarm using the swarm’s communication graph topology. Both single and multiple job site cases are explored. The results are compared against a full swarm movement method. Simulation results show that the proposed method outperforms a full swarm method in the average number of messages sent per robot in each step, as well as, the distance traveled by the swarm

Multi-robot team formation control in the GUARDIANS project

Purpose The GUARDIANS multi-robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots guide and accompany the firefighters on site whilst indicating possible obstacles and the locations of danger and maintaining communications links. Design/methodology/approach In order to fulfill the aforementioned tasks the robots need to exhibit certain behaviours. Among the basic behaviours are capabilities to stay together as a group, that is, generate a formation and navigate while keeping this formation. The control model used to generate these behaviours is based on the so-called social potential field framework, which we adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots. Findings The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus the application has forced us to redefine the concept of a formation. Using the graph-theoretic terminology, we can say that a formation may be stretched out as a path or be compact as a star or wheel. We have implemented the developed behaviours in simulation environments as well as on real ERA-MOBI robots commonly referred to as Erratics. We discuss advantages and shortcomings of our model, based on the simulations as well as on the implementation with a team of Erratics.</p

A Planning Pipeline for Large Multi-Agent Missions

In complex multi-agent applications, human operators are often tasked with planning and managing large heterogeneous teams of humans and autonomous vehicles. Although the use of these autonomous vehicles broadens the scope of meaningful applications, many of their systems remain unintuitive and difficult to master for human operators whose expertise lies in the application domain and not at the platform level. Current research focuses on the development of individual capabilities necessary to plan multi-agent missions of this scope, placing little emphasis on the integration of these components in to a full pipeline. The work presented in this paper presents a complete and user-agnostic planning pipeline for large multiagent missions known as the HOLII GRAILLE. The system takes a holistic approach to mission planning by integrating capabilities in human machine interaction, flight path generation, and validation and verification. Components modules of the pipeline are explored on an individual level, as well as their integration into a whole system. Lastly, implications for future mission planning are discussed

Behavior Mixing with Minimum Global and Subgroup Connectivity Maintenance for Large-Scale Multi-Robot Systems

In many cases the multi-robot systems are desired to execute simultaneously multiple behaviors with different controllers, and sequences of behaviors in real time, which we call \textit{behavior mixing}. Behavior mixing is accomplished when different subgroups of the overall robot team change their controllers to collectively achieve given tasks while maintaining connectivity within and across subgroups in one connected communication graph. In this paper, we present a provably minimum connectivity maintenance framework to ensure the subgroups and overall robot team stay connected at all times while providing the highest freedom for behavior mixing. In particular, we propose a real-time distributed Minimum Connectivity Constraint Spanning Tree (MCCST) algorithm to select the minimum inter-robot connectivity constraints preserving subgroup and global connectivity that are \textit{least likely to be violated} by the original controllers. With the employed safety and connectivity barrier certificates for the activated connectivity constraints and collision avoidance, the behavior mixing controllers are thus minimally modified from the original controllers. We demonstrate the effectiveness and scalability of our approach via simulations of up to 100 robots with multiple behaviors.Comment: To appear in Proceedings of IEEE International Conference on Robotics and Automation (ICRA) 202

Outdoor operations of multiple quadrotors in windy environment

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV system, each sUAV has to locally counter the wind disturbance while maintaining the safety of the system. Such continuous manipulation of the control effort for multiple sUAVs under uncertain environmental conditions is computationally taxing and can lead to reduced efficiency and safety concerns. Additionally, modern day sUAV systems are susceptible to cyberattacks due to their use of commercial wireless communication infrastructure. This dissertation aims to address these multi-faceted challenges related to the operation of outdoor rotor-based multi-sUAV systems. A comprehensive review of four representative techniques to measure and estimate wind speed and direction using rotor-based sUAVs is discussed. After developing a clear understanding of the role wind gusts play in quadrotor motion, two decentralized motion planners for a multi-quadrotor system are implemented and experimentally evaluated in the presence of wind disturbances. The first planner is rooted in the reinforcement learning (RL) technique of state-action-reward-state-action (SARSA) to provide generalized path plans in the presence of wind disturbances. While this planner provides feasible trajectories for the quadrotors, it does not provide guarantees of collision avoidance. The second planner implements a receding horizon (RH) mixed-integer nonlinear programming (MINLP) model that is integrated with control barrier functions (CBFs) to guarantee collision-free transit of the multiple quadrotors in the presence of wind disturbances. Finally, a novel communication protocol using Ethereum blockchain-based smart contracts is presented to address the challenge of secure wireless communication. The U.S. sUAV market is expected to be worth $92 Billion by 2030. The Association for Unmanned Vehicle Systems International (AUVSI) noted in its seminal economic report that UAVs would be responsible for creating 100,000 jobs by 2025 in the U.S. The rapid proliferation of drone technology in various applications has led to an increasing need for professionals skilled in sUAV piloting, designing, fabricating, repairing, and programming. Engineering educators have recognized this demand for certified sUAV professionals. This dissertation aims to address this growing sUAV-market need by evaluating two active learning-based instructional approaches designed for undergraduate sUAV education. The two approaches leverages the interactive-constructive-active-passive (ICAP) framework of engagement and explores the use of Competition based Learning (CBL) and Project based Learning (PBL). The CBL approach is implemented through a drone building and piloting competition that featured 97 students from undergraduate and graduate programs at NJIT. The competition focused on 1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, 2) simulation of drone flight missions, and 3) manual and semi-autonomous drone piloting were implemented. The effective student learning experience from this competition served as the basis of a new undergraduate course on drone science fundamentals at NJIT. This undergraduate course focused on the three foundational pillars of drone careers: 1) drone programming using Python, 2) designing and fabricating drones using Computer-Aided Design (CAD) and rapid prototyping, and 3) the US Federal Aviation Administration (FAA) Part 107 Commercial small Unmanned Aerial Vehicles (sUAVs) pilot test. Multiple assessment methods are applied to examine the students’ gains in sUAV skills and knowledge and student attitudes towards an active learning-based approach for sUAV education. The use of active learning techniques to address these challenges lead to meaningful student engagement and positive gains in the learning outcomes as indicated by quantitative and qualitative assessments

Providing incentive to peer-to-peer applications

Cooperative peer-to-peer applications are designed to share the resources of participating computers for the common good of ail users. However, users do not necessarily have an incentive to donate resources to the system if they can use the system's resources for free. As commonly observed in deployed applications, this situation adversely affects the applications' performance and sometimes even their availability and usability. While traditional resource management is handled by a centralized enforcement entity, adopting similar solution raises new concerns for distributed peer-to-peer systems. This dissertation proposes to solve the incentive problem in peer-to-peer applications by designing fair sharing policies and enforcing these policies in a distributed manner. The feasibility and practicability of this approach is demonstrated through numerous applications, namely archival storage systems, streaming systems, content distribution systems, and anonymous communication systems

Anthills Built to Order: Automating Construction with Artificial Swarms

PhD thesisSocial insects build large, complex structures, which emerge through the collective actions of many simple agents acting with no centralized control or preplanning. These natural systems motivate investigating the use of artificial swarms to automate construction or fabrication. The goal is to be able to take an unspecified number of simple robots and a supply of building material, give the system a high-level specification for any arbitrary structure desired, and have a guarantee that it will produce that structure without further intervention.In this thesis I describe such a distributed system for automating construction, in which autonomous mobile robots collectively build user-specified structures from square building blocks. The approach preserves many desirable features of the natural systems, such as considerable parallelism and robustness to factorslike robot loss and variable order or timing of actions. Further, unlike insect colonies, it can build particular desired structures according to a high-level design provided by the user.Robots in this system act without explicit communication or cooperation, instead using the partially completed structure to coordinate their actions. This mechanism is analogous to that of stigmergy used by social insects, in which insects take actions that affect the environment, and the environmental state influences further actions. I introduce a framework of "extended stigmergy" in which building blocks are allowed to store, process or communicate information. Increasing the capabilities of the building material (rather than of the robots) in this way increases the availability of nonlocal structure information. Benefits include significant improvements in construction speed and in ability to take advantage of the parallelism of the swarm.This dissertation describes system design and control rules for decentralized teams of robots that provably build arbitrary solid structures in two dimensions. I present a hardware prototype, and discuss extensions to more general structures, including those built with multiple block types and in three dimensions

Anthills built to order : automating construction with artificial swarms

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (leaves 110-116).Social insects build large, complex structures, which emerge through the collective actions of many simple agents acting with no centralized control or preplanning. These natural systems motivate investigating the use of artificial swarms to automate construction or fabrication. The goal is to be able to take an unspecified number of simple robots and a supply of building material, give the system a high-level specification for any arbitrary structure desired, and have a guarantee that it will produce that structure without further intervention. In this thesis I describe such a distributed system for automating construction, in which autonomous mobile robots collectively build user-specified structures from square building blocks. The approach preserves many desirable features of the natural systems, such as considerable parallelism and robustness to factors like robot loss and variable order or timing of actions. Further, unlike insect colonies, it can build particular desired structures according to a high-level design provided by the user. Robots in this system act without explicit communication or cooperation, instead using the partially completed structure to coordinate their actions.(cont.) This mechanism is analogous to that of stigmergy used by social insects, in which insects take actions that affect the environment, and the environmental state influences further actions. I introduce a framework of extended stigmergy in which building blocks are allowed to store, process or communicate information. Increasing the capabilities of the building material (rather than of the robots) in this way increases the availability of nonlocal structure information. Benefits include significant improvements in construction speed and in ability to take advantage of the parallelism of the swarm. This dissertation describes system design and control rules for decentralized teams of robots that provably build arbitrary solid structures in two dimensions. I present a hardware prototype, and discuss extensions to more general structures, including those built with multiple block types and in three dimensions.by Justin Werfel.Ph.D

Scaling Permissioned Blockchains via Sharding

Traditional distributed systems, such as those used in banking and real estate, require a trusted third party to operate and maintain them, which is highly dependent on the reliability of the operator. Since Bitcoin was introduced by Nakamoto in 2008, blockchain technology has been considered as a promising solution to the trust issue raised by the traditional centralized approach.Blockchain is now used by most cryptocurrencies and has meaningful applications in other areas, such as logistics and supply chain management. However, scalability remains a major limitation. Various techniques are being investigated to tackle the scalability issue. Sharding is an intuitive approach to improve the scalability of blockchain systems. This thesis explores sharding techniques in permissioned blockchains. First of all, two techniques are examined for interleaving the shards of permissioned blockchains, which are referred to as strong temporal coupling and weak temporal coupling. The analysis and experiment results show that strong coupling loses performance when different shards grow unevenly, but outperforms weak coupling in a wide-area environment due to its inherent efficiency. Weak coupling, in contrast, deals naturally with load imbalance across shards and in fact tolerates shard failures without any additional effort, but loses performance when running on a high-latency network due to the additional coordination performed. Second, we propose Antipaxos, a leaderless consensus protocol that reaches agreement on multiple proposals with a fast path solution in the failure-free case, and falls back on a slow path to handle other cases. A new agreement problem, termed as k-Interactive Consistency is formalized first. Then, two algorithms to solve this problem are proposed under the crash failure model and Byzantine failure model, respectively. We prove the safety and liveness of the proposed algorithms, and present an experimental evaluation of their performance in the Amazon cloud. Both the crash-tolerant and Byzantine-tolerant designs reach agreement on n batches of proposals with Θ(n2) messages. This leads to the linear complexity of each batch in one consensus cycle, rather than a single batch of proposals per cycle in conventional solutions. The experiments show that our algorithms achieve not only lower execution latency but also higher peak throughput in the failure-free case when deployed in a geo-distributed environment. Lastly, we introduce a full sharding protocol, Geochain, for permissioned blockchains. The transaction latency is minimized by clustering participants using their geographical properties--locality. In addition, the locality is also being used to decide the transaction placement which suggests a low ratio of cross-shard transactions for applications, such as everyday banking, retail payments, and electric vehicle charging. We also propose a client-driven efficient mechanism to handle cross-shard transactions and present an analysis. This enables clients to manage their assets across different shards directly. A prototype is implemented on top of Hyperleder Fabric v2.3 and evaluated on Amazon EC2. The experiments show that our protocol doubles the peak throughput even with a high ratio of cross-shard transactions while minimizing the transaction latency