Constrained Consensus in Continuous-Time Multi-Agent Systems

Since the consensus problem is getting popular in recent researches and the applications based on it are expanding in current years! the consensus problem under the condition that constraints exist on agents’ state in continuous-time in a multi-agent system has been studied here. This work combines the projection operator method in a general consensus algorithm to avoid the violation of state on its individual constraint set. When the projection operator works in the general consensus algorithm, the constraint region is divided into the projection-operator working region and the non-projection region. The boundary between these two regions is a circular line. Once the state of the correspond agent cross this line, the projection operator starts to work when the state is going out from the non-projection region and moves towards to its constraint boundary. The boundary of the starting circle for projection opera- tor has the same shape with the constraint set boundary. The difference is it has a smaller area with a certain ratio. With a one dimensional projection-based consensus algorithm, we analyzed the projection-based consensus algorithm on the expected-to- arrival (ETA) requirement which is always the problem at the simultaneous arrival task on multiple unmanned aerial vehicles (UAVs) system. The stability and con- vergence rate of the proposed algorithm has been analyzed. Based on the stability and convergence rate, the conditions to guarantee the feasibility of the simultaneous arrival task has also been presented. Then the analysis for projection-based consensus algorithm has been extended in a high dimensions, in this case, the agents can only exchange their state information in continuous time in a connected and undirected communication network topology. The result is proven that since the intersection set of every state constraint is non-empty, the global consensus will eventually be achieved. At last, the projection-based algorithm has been applied on a UAV module, with the UAV dynamics, the algorithm makes a multi-UAV system with different ability in flying reach the global spatial consensus achievement for simultaneous arrival task

Motion Planning

Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms

Group of UAVs Moving on Smooth Control Law with Fixed Obstacles

In this paper considered the movement of multi-agent system that consists of several UAVs that carry out monitoring ground surface. The multi-agent system includes a lead agent and several agents-members of the group. The motion of this system occurs along a trajectory, which is determined by the initial conditions, its mathematical model and obstacles on the route. Only the leader of the group knows the ultimate goal of the movement. The motion of this structure is considered in the potential field, which determined the forces of attraction and repulsion and created control signals by measuring the distances to the nearest neighbors. This allows the UAV group to consider an aggregate that has some size and to describe its motion the system of differential equations of second-order. As UAV selected Quadrotor. In this investigation, the stability conditions of such motion are considered, and simulation of approach is proposed.In this paper considered the movement of multi-agent system that consists of several UAVs that carry out monitoring ground surface. The multi-agent system includes a lead agent and several agents-members of the group. The motion of this system occurs along a trajectory, which is determined by the initial conditions, its mathematical model and obstacles on the route. Only the leader of the group knows the ultimate goal of the movement. The motion of this structure is considered in the potential field, which determined the forces of attraction and repulsion and created control signals by measuring the distances to the nearest neighbors. This allows the UAV group to consider an aggregate that has some size and to describe its motion the system of differential equations of second-order. As UAV selected Quadrotor. In this investigation, the stability conditions of such motion are considered, and simulation of approach is proposed

Modeling and control of UAV bearing formations with bilateral high-level steering

In this paper we address the problem of controlling the motion of a group of unmanned aerial vehicles (UAVs) bound to keep a formation defined in terms of only relative angles (i.e. a bearing formation). This problem can naturally arise within the context of several multi-robot applications such as, e.g. exploration, coverage, and surveillance. First, we introduce and thoroughly analyze the concept and properties of bearing formations, and provide a class of minimally linear sets of bearings sufficient to uniquely define such formations. We then propose a bearing-only formation controller requiring only bearing measurements, converging almost globally, and maintaining bounded inter-agent distances despite the lack of direct metric information.The controller still leaves the possibility of imposing group motions tangent to the current bearing formation. These can be either autonomously chosen by the robots because of any additional task (e.g. exploration), or exploited by an assisting human co-operator. For this latter 'human-in-the-loop' case, we propose a multi-master/multi-slave bilateral shared control system providing the co-operator with some suitable force cues informative of the UAV performance. The proposed theoretical framework is extensively validated by means of simulations and experiments with quadrotor UAVs equipped with onboard cameras. Practical limitations, e.g. limited field-of-view, are also considered. © The Author(s) 2012

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

A Survey of path following control strategies for UAVs focused on quadrotors

The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.Peer ReviewedPostprint (author's final draft

Coordination of Multirobot Teams and Groups in Constrained Environments: Models, Abstractions, and Control Policies

Robots can augment and even replace humans in dangerous environments, such as search and rescue and reconnaissance missions, yet robots used in these situations are largely tele-operated. In most cases, the robots\u27 performance depends on the operator\u27s ability to control and coordinate the robots, resulting in increased response time and poor situational awareness, and hindering multirobot cooperation. Many factors impede extended autonomy in these situations, including the unique nature of individual tasks, the number of robots needed, the complexity of coordinating heterogeneous robot teams, and the need to operate safely. These factors can be partly addressed by having many inexpensive robots and by control policies that provide guarantees on convergence and safety. In this thesis, we address the problem of synthesizing control policies for navigating teams of robots in constrained environments while providing guarantees on convergence and safety. The approach is as follows. We first model the configuration space of the group (a space in which the robots cannot violate the constraints) as a set of polytopes. For a group with a common goal configuration, we reduce complexity by constructing a configuration space for an abstracted group state. We then construct a discrete representation of the configuration space, on which we search for a path to the goal. Based on this path, we synthesize feedback controllers, decentralized affine controllers for kinematic systems and nonlinear feedback controllers for dynamical systems, on the polytopes, sequentially composing controllers to drive the system to the goal. We demonstrate the use of this method in urban environments and on groups of dynamical systems such as quadrotors. We reduce the complexity of multirobot coordination by using an informed graph search to simultaneously build the configuration space and find a path in its discrete representation to the goal. Furthermore, by using an abstraction on groups of robots we dissociate complexity from the number of robots in the group. Although the controllers are designed for navigation in known environments, they are indeed more versatile, as we demonstrate in a concluding simulation of six robots in a partially unknown environment with evolving communication links, object manipulation, and stigmergic interactions