273 research outputs found

    Full-Body Torque-Level Non-linear Model Predictive Control for Aerial Manipulation

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    Non-linear model predictive control (nMPC) is a powerful approach to control complex robots (such as humanoids, quadrupeds, or unmanned aerial manipulators (UAMs)) as it brings important advantages over other existing techniques. The full-body dynamics, along with the prediction capability of the optimal control problem (OCP) solved at the core of the controller, allows to actuate the robot in line with its dynamics. This fact enhances the robot capabilities and allows, e.g., to perform intricate maneuvers at high dynamics while optimizing the amount of energy used. Despite the many similarities between humanoids or quadrupeds and UAMs, full-body torque-level nMPC has rarely been applied to UAMs. This paper provides a thorough description of how to use such techniques in the field of aerial manipulation. We give a detailed explanation of the different parts involved in the OCP, from the UAM dynamical model to the residuals in the cost function. We develop and compare three different nMPC controllers: Weighted MPC, Rail MPC, and Carrot MPC, which differ on the structure of their OCPs and on how these are updated at every time step. To validate the proposed framework, we present a wide variety of simulated case studies. First, we evaluate the trajectory generation problem, i.e., optimal control problems solved offline, involving different kinds of motions (e.g., aggressive maneuvers or contact locomotion) for different types of UAMs. Then, we assess the performance of the three nMPC controllers, i.e., closed-loop controllers solved online, through a variety of realistic simulations. For the benefit of the community, we have made available the source code related to this work.Comment: Submitted to Transactions on Robotics. 17 pages, 16 figure

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

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    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

    Advanced Strategies for Robot Manipulators

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    Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

    Robust Intelligent Sensing and Control Multi Agent Analysis Platform for Research and Education

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    The aim of this thesis is the development and implementation of a controlled testing platform for the Robust Intelligent Sensing and Controls (RISC) Lab at Utah State University (USU). This will be an open source adaptable expandable robotics platform usable for both education and research. This differs from the many other platforms developed in that the entire platform software will be made open source. This open source software will encourage collaboration among other universities and enable researchers to essentially pick up where others have left off without the necessity of replicating months or even years of work. The expected results of this research will create a foundation for diverse robotics investigation at USU as well as enable attempts at novel methods of control, estimation and optimization. This will also contribute a complete software testbed setup to the already vibrant robotics open source research community. This thesis first outlines the platform setup and novel developments therein. The second stage provides an example of how this has been used in education, providing an example curriculum implementing modern control techniques. The third section provides some exploratory research in trajectory control and state estimation of the tip of an inverted pendulum atop a small unmanned aerial vehicle as well as bearing-only cooperative localization experimentation. Finally, a conclusion and future work is discussed

    Unmanned Robotic Systems and Applications

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    This book presents recent studies of unmanned robotic systems and their applications. With its five chapters, the book brings together important contributions from renowned international researchers. Unmanned autonomous robots are ideal candidates for applications such as rescue missions, especially in areas that are difficult to access. Swarm robotics (multiple robots working together) is another exciting application of the unmanned robotics systems, for example, coordinated search by an interconnected group of moving robots for the purpose of finding a source of hazardous emissions. These robots can behave like individuals working in a group without a centralized control

    Function Design of Mechatronic Systems for Human-Robot Collaboration

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    Traditionally, robots have been caged off from human activity but, recently, improvements in advance robotic technology as well as the introduction of new safety standards, have allowed the possibility of collaboration between human workers and robotic systems. The introduction of Human-Robot Collaboration has the potential to increase the quality and the flexibility of the production process while improving the working condition of the operators. However, traditional industrial robots are typically characterized by small payload and small reachable workspace that reduce the range of possible applications. These drawbacks can overcome the advantages related to a collaborative task and make the collaboration not effective. This work aims at analyzing innovative mechatronic solutions capable of increasing the workspace and the versatility of the system with the final goal of creating effective collaborations with humans. Cable driven Parallel Robots (CDPRs) are considered a promising technology able to satisfy these requirements. In fact, compared to rigid serial and parallel robots, they have several advantages such as large workspaces, high payloads per unit of weight, ease of construction, versatility and affordable costs. This work presents two innovative solutions of CDPR able to enlarge the workspace, improve the versatility and reduce the collisions risk. The first solution consists of a cable-suspended parallel robot with a reconfigurable end-effector whereas the second solution is an innovative model of cable-driven micro-macro robot. In the first part of the thesis, the kinematic and dynamic models of these innovative systems are presented and analyzed in order to characterize their capability. Trajectory planning and optimal design are addressed with the purpose of maximizing the performance of the systems. The last part of the thesis deals with the design of a novel family of Intelligent CAble-driven parallel roBOTs whose architecture and control are conceived to maximize the robot versatility to the task to be performed and the environment in which the robot is intended to operate

    New Approaches in Automation and Robotics

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    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

    Automation and Robotics: Latest Achievements, Challenges and Prospects

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    This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections
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