An Incrementally Deployed Swarm of MAVs for Localization UsingUltra-Wideband

Knowing the position of a moving target can be crucial, for example when localizing a first responder in an emergency scenario. In recent years, ultra wideband (UWB) has gained a lot of attention due to its localization accuracy. Unfortunately, UWB solutions often demand a manual setup in advance. This is tedious at best and not possible at all in environments with access restrictions (e.g., collapsed buildings). Thus, we propose a solution combining UWB with micro air vehicles (MAVs) to allow for UWB localization in a priori inaccessible environments. More precisely, MAVs equipped with UWB sensors are deployed incrementally into the environment. They localize themselves based on previously deployed MAVs and on-board odometry, before they land and enhance the UWB mesh network themselves. We tested this solution in a lab environment using a motion capture system for ground truth. Four MAVs were deployed as anchors and a fifth MAV was localized for over 80 second at a root mean square (RMS) of 0.206 m averaged over five experiments. For comparison, a setup with ideal anchor position knowledge came with 20 % lower RMS, and a setup purely based on odometry with 81 % higher RMS. The absolute scale of the error with the proposed approach is expected to be low enough for applications envisioned within the scope of this paper (e.g., the localization of a first responder) and thus considered a step towards flexible and accurate localization in a priori inaccessible, GNSS-denied environments.acceptedVersio

Distributed MPC for Formation Path-Following of Multi-Vehicle Systems

The paper considers the problem of formation path-following of multiple vehicles and proposes a solution based on combining distributed model predictive control with parametrizations of the trajectories of the vehicles using polynomial splines. Introducing such parametrization leads indeed to two potential benefits: A) reducing the number of optimization variables, and b) enabling enforcing constraints on the vehicles in a computationally efficient way. Moreover, the proposed solution formulates the formation path-following problem as a distributed optimization problem that may then be solved using the alternating direction method of multipliers (ADMM). The paper then analyzes the effectiveness of the proposed method via numerical simulations with surface vehicles and differential drive robotspublishedVersio

Singularity-free Formation Path Following of Underactuated AUVs: Extended Version

This paper proposes a method for formation path following control of a fleet of underactuated autonomous underwater vehicles. The proposed method combines several hierarchic tasks in a null space-based behavioral algorithm to safely guide the vehicles. Compared to the existing literature, the algorithm includes both inter-vehicle and obstacle collision avoidance, and employs a scheme that keeps the vehicles within given operation limits. The algorithm is applied to a six degree-of-freedom model, using rotation matrices to describe the attitude to avoid singularities. Using the results of cascaded systems theory, we prove that the closed-loop system is uniformly semiglobally exponentially stable. We use numerical simulations to validate the results.Comment: Extended version of a paper, to appear in Proc. 2023 IFAC World Congress, 13 pages (9p + 4p appendices), 5 figure

Control of Under-actuated Marine Vehicles

In this dissertation, various topics related to control problems for under-actuated marine vehicles are investigated. The thesis is divided into three parts. The first part deals with the source-seeking problem for multi-agent systems. It is assumed that a group of vehicles has to identify the location of a source in the ocean space. The source may for instance be an area with a high concentration of a specific chemical substance. The agents have to define the direction of motion towards the source utilizing distributed measurements of the scalar field surrounding the source. It is supposed that the agents are organized in a leaderfollower scheme. An approach for kinematic unicycle agents is first presented. In this approach the novelty is a variable-leader scheme. That is, it is assumed that the leader can change during the mission. This allows for a better distribution of the tasks in the group. In particular, there is an agent in the group which has information about the direction where to move in order to explore an area of interest. Then there is also another agent that can take on the role as leader if it gets satisfactory measurements from the environment. This approach is then used in order to develop a strategy for multi-agent systems consisting of under-actuated marine vehicles. In this second case, a synchronization controller is used for the vehicles in order to achieve motion in formation. The leader agent collects information from the followers and is able to compute the direction pointing towards the source, computing the approximated gradient of the field surrounding the source. Simulation case studies are presented in order to validate the approaches. In the second part of the thesis a novel approach for controlling under-actuated marine vehicles is presented. The approach is inspired by works on control of nonholonomic ground vehicles. The method is based on the definition of a different output for the system. Then an input-output feedback linearization controller is used in order to apply a change of inputs to the system. This methods transforms the nonlinear model an under-actuated marine vehicle into a system with a linear external dynamics and a nonlinear internal dynamics. We use this approach to solve the trajectory tracking control problem, the path following control problem and the leader-follower synchronization control problem for marine vehicles in presence of environmental disturbances. Simulation case studies and experimental results validate the theoretical results. The third part of the thesis deals with the path following control problem for under-actuated marine vehicles. First the path following control problem is dealt with for unparametrized straight-line paths. A guidance law inspired by a common control approach for aerial vehicles is developed. The guidance is based on geometric control principles and it is used together with an observer in order to counteract the effect of ocean currents. Almost-global stability of the closedloop system is proven and a simulation case study validates the theoretical result. Then the path following problem for curved paths is considered. In particular, paths parametrized by a path variable are considered. Two strategies are considered. Both the strategy are based on a parametrization of the curve which is used to propagate a path-tangential frame. The path following errors are defined with respect to the path-tangential frame. The first strategy forces the vehicle to move along the normal of the path-tangential frame. This results in a singularity which makes the strategy valid only locally around the path. The second strategy defines a different path parametrization which is valid globally. Here an ocean current observer is also used in order to counteract the ocean current disturbance. The closed-loop system is proven to be globally asymptotically stable. The theoretical results are verified via numerical simulations. Finally, a novel control strategy for path following of curved paths is presented. The novelty of this last approach is that it does not require any parametrization of the path. In fact, the path is implicitly defined as a manifold in the state space. The control approach is based on geometric control and hierarchical control design. An adaptive controller is used in order to deal with the disturbance caused by ocean currents. The closed-loop system is proven to be asymptotically stable

Source Seeking With a Variable Leader Multi-Agent Fixed Topology Network

In this paper a source seeking method for multi-agent systems organized with the Leader-Follower scheme is studied. Our objective is to develop a controller for the headings of the agents. The group of agents is characterized by an initial leader, which steers all the agents towards an initial given heading. Another agent, an active follower, can take on the role as leader if it gets satisfactory measures from the environment. If the active follower becomes leader, it steers the whole group towards the source present in the field. We focus on a 2D case, and simulation results are reported to illustrate and validate theoretical results

Micro indoor-drones (MINs) for localization of first responders

In this paper, we describe our approach to the localization in GNSS-denied and risky unknown environments of first responders (FRs). The INGENIOUS project is an EU funded project which is developing a new integrated toolkit to support the operations of FRs. The micro indoor-drones (MINs) developed within the INGENIOUS project represent a component of the toolkit which will support the localization of FRs in search-and-rescue (SAR) operations. In this paper, the concept behind the MINs and the current achievements are illustrated

Micro indoor-drones (MINs) for localization of first responders

In this paper, we describe our approach to the localization in GNSS-denied and risky unknown environments of first responders (FRs). The INGENIOUS project is an EU funded project which is developing a new integrated toolkit to support the operations of FRs. The micro indoor-drones (MINs) developed within the INGENIOUS project represent a component of the toolkit which will support the localization of FRs in search-and-rescue (SAR) operations. In this paper, the concept behind the MINs and the current achievements are illustrated.publishedVersio

Distributed MPC for Formation Path-Following of Multi-Vehicle Systems

The paper considers the problem of formation path-following of multiple vehicles and proposes a solution based on combining distributed model predictive control with parametrizations of the trajectories of the vehicles using polynomial splines. Introducing such parametrization leads indeed to two potential benefits: a) reducing the number of optimization variables, and b) enabling enforcing constraints on the vehicles in a computationally efficient way. Moreover, the proposed solution formulates the formation path-following problem as a distributed optimization problem that may then be solved using the alternating direction method of multipliers (ADMM). The paper then analyzes the effectiveness of the proposed method via numerical simulations with surface vehicles and differential drive robots

Distributed MPC for Formation Path-Following of Multi-Vehicle Systems

The paper considers the problem of formation path-following of multiple vehicles and proposes a solution based on combining distributed model predictive control with parametrizations of the trajectories of the vehicles using polynomial splines. Introducing such parametrization leads indeed to two potential benefits: A) reducing the number of optimization variables, and b) enabling enforcing constraints on the vehicles in a computationally efficient way. Moreover, the proposed solution formulates the formation path-following problem as a distributed optimization problem that may then be solved using the alternating direction method of multipliers (ADMM). The paper then analyzes the effectiveness of the proposed method via numerical simulations with surface vehicles and differential drive robot