A control architecture and human interface for agile, reconfigurable micro aerial vehicle formations

This thesis considers the problem of controlling a group of micro aerial vehicles for agile maneuvering cooperatively, or distributively. We first introduce the background and motivation for micro aerial vehicles, especially for the popular multi-rotor aerial vehicle platform. Then, we discuss the dynamics of quadrotor helicopters. A quadrotor is a specific kind of multi-rotor aerial vehicle with a special property called differential flatness, which simplifies the algorithm of trajectory planning, such that, instead of planning a trajectory in a 12-dimensional state space and 4-dimensional input space, we only need to plan the trajectory in 4-dimensional, so called, flat output space, while the 12-dimensional state and 4-dimensional input can be recovered from a mapping called endogenous transformation. We propose a series of approaches to achieve agile maneuvering of a dynamic quadrotor formation, from controlling a single quadrotor in an artificial vector field, to controlling a group of quadrotors in a Virtual Rigid Body (VRB) framework, to balancing the effect between the human control and autonomy for collision avoidance, and to fast on-line distributed collision avoidance with Buffered Voronoi Cells (BVC). In the vector field method, we generate velocity, acceleration, jerk and snap fields, depending on the tasks, or the positions of obstacles, such that a single quadrotor can easily find its required state and input from the endogenous transformation in order to track the artificial vector field. Next, with a Virtual Rigid Body framework, we let a group of quadrotors follow a single control command while also keeping a required formation, or even reconfigure from one formation to another. The Virtual Rigid Body framework decouples the trajectory planning problem into two sub-problems. Then we consider the problem of collision avoidance of the quadrotor formation when it is meanwhile tele-operated by a single human operator. The autonomy with collision avoidance algorithm, based on the vector field methods for a single quadrotor, is an assistive portion of the quadrotor formation controller, such that the human operator can focus on his/her high-level tasks, leaving the low-level collision avoidance task be handled automatically. We also consider the full autonomy problem of quadrotor formations when reconfiguring from one formation to another by developing a fast, on-line distributed collision avoidance algorithm using Buffered Voronoi Cells (BVCs). Our BVC based collision avoidance algorithm only requires sensed relative position, rather than relative position and velocity, while the computational complexity is comparable to other methods like velocity obstacles. At last, we introduce our experimental quadrotor platform which is built from PixHawk flight controller and Odroid-XU4 single-board computer. The hardware and software architecture of this multiple-quadrotor platform is described in detail so that our platform can easily be adopted and extended with different purposes. Our conclusion remark and discussion of future work are also given in this thesi

Aerial Manipulation: A Literature Review

Aerial manipulation aims at combining the versatil- ity and the agility of some aerial platforms with the manipulation capabilities of robotic arms. This letter tries to collect the results reached by the research community so far within the field of aerial manipulation, especially from the technological and control point of view. A brief literature review of general aerial robotics and space manipulation is carried out as well

Trajectory tracking and time delay management of 4-mecanum wheeled mobile robots (4-MWMR)

International audienceNowadays, wheeled mobile robots have a very important role in industrial applications, namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper deals with the time delay management, the trajectory generation and the tracking problem applied on four wheeled omnidirectional mobile robots. A strategy is proposed to minimize or compensate the time delay caused by obstacles. The approach is done by updating the reference trajectory. This update helps to track the trajectory in real time, a new control law based on the feedback linearization control theory is synthesized to track perfectly generated or updated trajectories

Learning-based Predictive Path Following Control for Nonlinear Systems Under Uncertain Disturbances

Accurate path following is challenging for autonomous robots operating in uncertain environments. Adaptive and predictive control strategies are crucial for a nonlinear robotic system to achieve high-performance path following control. In this paper, we propose a novel learning-based predictive control scheme that couples a high-level model predictive path following controller (MPFC) with a low-level learning-based feedback linearization controller (LB-FBLC) for nonlinear systems under uncertain disturbances. The low-level LB-FBLC utilizes Gaussian Processes to learn the uncertain environmental disturbances online and tracks the reference state accurately with a probabilistic stability guarantee. Meanwhile, the high-level MPFC exploits the linearized system model augmented with a virtual linear path dynamics model to optimize the evolution of path reference targets, and provides the reference states and controls for the low-level LB-FBLC. Simulation results illustrate the effectiveness of the proposed control strategy on a quadrotor path following task under unknown wind disturbances.Comment: 8 pages, 7 figures, accepted for publication in IEEE Robotics and Automation Letters ( Volume: 6, Issue: 2, April 2021

Velocity constrained trajectory generation for a collinear Mecanum wheeled robot

While much research has been conducted into the generation of smooth trajectories for underactuated unstable aerial vehicles such as quadrotors, less attention has been paid to the application of the same techniques to ground based omnidirectional dynamically balancing robots. These systems have more control authority over their linear accelerations than aerial vehicles, meaning trajectory smoothness is less of a critical design parameter. However, when operating in indoor environments these systems must often adhere to relatively low velocity constraints, resulting in very conservative trajectories when enforced using existing trajectory optimisation methods. This paper makes two contributions; this gap is bridged by the extension of these existing methods to create a fast velocity constrained trajectory planner, with trajectory timing characteristics derived from the optimal minimum-time solution of a simplified acceleration and velocity constrained model. Next, a differentially flat model of an omnidirectional balancing robot utilizing a collinear Mecanum drive is derived, which is used to allow an experimental prototype of this configuration to smoothly follow these velocity constrained trajectories

New Approaches in Automation and Robotics

The book New Approaches in Automation and Robotics offers in 22 chapters a collection of recent developments in automation, robotics as well as control theory. It is dedicated to researchers in science and industry, students, and practicing engineers, who wish to update and enhance their knowledge on modern methods and innovative applications. The authors and editor of this book wish to motivate people, especially under-graduate students, to get involved with the interesting field of robotics and mechatronics. We hope that the ideas and concepts presented in this book are useful for your own work and could contribute to problem solving in similar applications as well. It is clear, however, that the wide area of automation and robotics can only be highlighted at several spots but not completely covered by a single book

Dynamic path following controllers for planar mobile robots

In the field of mobile robotics, many applications require feedback control laws that provide perfect path following. Previous work has shown that transverse feedback linearization is an effective approach to designing path following controllers that achieve perfect path following and path invariance. This thesis uses transverse feedback linearization and augments it with dynamic extension to present a framework for designing path following controllers for certain kinematic models of mobile robots. This approach can be used to design path following controllers for a large class of paths. While transverse feedback linearization makes the desired path attractive and invariant, dynamic extension allows the closed-loop system to achieve the desired motion along the path. In particular, dynamic extension can be used to make the mobile robot track a desired velocity or acceleration profile while moving along a path