A Combination of PD Controller and PIAFC for Stabilization of “x†Configuration Quadcopter

This paper presents a stabilization control method for “x†configuration quadcopter. The control method used the combination of PD (Proportional Derivative) controller and PIAFC (Proportional Integral Active Force Control). PD is used to stabilize quadcopter, and PIAFC is used to reject uncertainty disturbance (e.g. wind) by estimating disturbance torque value of quadcopter. The PD with PIAFC provided better result where PIAFC could minimize uncertain disturbance effect. The simulation has successfully give comparation about controller performance (PD, PD-AFC, PD-PIAFC) by calculate RMS (Root Mean Square) value. PD with AFC gives better result than PD. AFC optimization using PI (PD-PIAFC) give best result if compared with PD or PD-AFC. PD-PIAFC has lowest RMS value of result control signal, 0.0389 for constant disturbance and 0.1008 for fluctuated disturbance.Keywords:“x†configuration quadcopter, stability, PD, PIAFC

Biologically inspired digital fabrication

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 37-40).Objects and systems in nature are models for the practice of sustainable design and fabrication. From trees to bones, natural systems are characterized by the constant interplay of creation, environmental response, and analysis of current structural constituents, as part of a larger dynamic system. In contrast, traditional methods of digital design and fabrication are characterized by a linear progression of three main stages: modeling (digital generation in the digital domain), analysis (digital mapping of the physical domain), and fabrication (physical generation of the digital domain). Moving towards a system process where modeling, analysis, and fabrication are integrated together for the development of a dynamic process will transform traditional fabrication technology and bring about the creation of sustainable and more efficient synthetic environments. Integration of modeling, analysis, and fabrication into one fluid process requires the development of a fabrication platform with capabilities for real time control. This thesis explores and investigates the creation of a framework for real time control of industrial robotic arms as part of a multipurpose fabrication platform.by Sarah Han.M. Eng

GATSBI: An Online GTSP-Based Algorithm for Targeted Surface Bridge Inspection

We study the problem of visually inspecting the surface of a bridge using an Unmanned Aerial Vehicle (UAV) for defects. We do not assume that the geometric model of the bridge is known. The UAV is equipped with a LiDAR and RGB sensor that is used to build a 3D semantic map of the environment. Our planner, termed GATSBI, plans in an online fashion a path that is targeted towards inspecting all points on the surface of the bridge. The input to GATSBI consists of a 3D occupancy grid map of the part of the environment seen by the UAV so far. We use semantic segmentation to segment the voxels into those that are part of the bridge and the surroundings. Inspecting a bridge voxel requires the UAV to take images from a desired viewing angle and distance. We then create a Generalized Traveling Salesperson Problem (GTSP) instance to cluster candidate viewpoints for inspecting the bridge voxels and use an off-the-shelf GTSP solver to find the optimal path for the given instance. As more parts of the environment are seen, we replan the path. We evaluate the performance of our algorithm through high-fidelity simulations conducted in Gazebo. We compare the performance of this algorithm with a frontier exploration algorithm. Our evaluation reveals that targeting the inspection to only the segmented bridge voxels and planning carefully using a GTSP solver leads to more efficient inspection than the baseline algorithms.Comment: 8 pages, 16 figure

Learning Control of Fixed-Wing Unmanned Aerial Vehicles Using Fuzzy Neural Networks

A learning control strategy is preferred for the control and guidance of a fixed-wing unmanned aerial vehicle to deal with lack of modeling and flight uncertainties. For learning the plant model as well as changing working conditions online, a fuzzy neural network (FNN) is used in parallel with a conventional P (proportional) controller. Among the learning algorithms in the literature, a derivative-free one, sliding mode control (SMC) theory-based learning algorithm, is preferred as it has been proved to be computationally efficient in real-time applications. Its proven robustness and finite time converging nature make the learning algorithm appropriate for controlling an unmanned aerial vehicle as the computational power is always limited in unmanned aerial vehicles (UAVs). The parameter update rules and stability conditions of the learning are derived, and the proof of the stability of the learning algorithm is shown by using a candidate Lyapunov function. Intensive simulations are performed to illustrate the applicability of the proposed controller which includes the tracking of a three-dimensional trajectory by the UAV subject to time-varying wind conditions. The simulation results show the efficiency of the proposed control algorithm, especially in real-time control systems because of its computational efficiency

Accelerating Power Grid Monitoring with Flying Robots and Artificial Intelligence

The digital revolution is expected to surpass all previous economic transformations in scale, scope, and complexity. Digital technologies are making electrical grids more connected, more reliable, and sustainable. Several efforts have been made to revamp the electric grid and modernize century-old systems. In the near future, we expect to see a revolution in power grind monitoring with incredible results through artificial intelligence and big data, drones, among others. The business opportunity for using drones in the energy sector is impressive, although very few companies have joined in its implementation. The drone allows the safe remote overflight of high voltage power lines. They can be deployed to detect, inspect, and diagnose the defects of the power line infrastructure. In this article, we provide the state of the art of using drones in smart grid monitoring. We demonstrate and propose an architecture based on Faster R-CNN for detecting ice accretion on power lines. Finally, we shed light on opportunities and future trends of these emerging technologies that can guide future research directions

Vertical infrastructure inspection using a quadcopter and shared autonomy control

This paper presents a shared autonomy control scheme for a quadcopter that is suited for inspection of vertical infrastructure — tall man-made structures such as streetlights, electricity poles or the exterior surfaces of buildings. Current approaches to inspection of such structures is slow, expensive, and potentially hazardous. Low-cost aerial platforms with an ability to hover now have sufficient payload and endurance for this kind of task, but require significant human skill to fly. We develop a control architecture that enables synergy between the ground-based operator and the aerial inspection robot. An unskilled operator is assisted by onboard sensing and partial autonomy to safely fly the robot in close proximity to the structure. The operator uses their domain knowledge and problem solving skills to guide the robot in difficult to reach locations to inspect and assess the condition of the infrastructure. The operator commands the robot in a local task coordinate frame with limited degrees of freedom (DOF). For instance: up/down, left/right, toward/away with respect to the infrastructure. We therefore avoid problems of global mapping and navigation while providing an intuitive interface to the operator. We describe algorithms for pole detection, robot velocity estimation with respect to the pole, and position estimation in 3D space as well as the control algorithms and overall system architecture. We present initial results of shared autonomy of a quadrotor with respect to a vertical pole and robot performance is evaluated by comparing with motion capture data

Sistema de enlace robusto para la teleoperación de un UAV (vehículo aéreo no tripulado) en la plataforma robótica ARGOS

Este proyecto consiste en la creación de un sistema de teleoperación para un UAV de tipo cuadricóptero. Para ello se diseñan los enlaces inalámbricos para la transmisión de señal de vídeo y de datos, para lo cual se ha estudiado la amplia oferta de módulos disponibles en el mercado y se ha seleccionado el conjunto adecuado para la fase de desarrollo inicial del proyecto. El sistema de transmisión de vídeo consiste en dos enlaces separados capaces de trabajar a la vez gracias al uso de antenas con polarizaciones ortogonales en cada uno de los enlaces. De esta forma, el UAV podrá ir equipado con dos cámaras de vídeo y transmitir ambas señales de forma simultánea. El enlace de datos se implementa utilizando dos módulos XBee, que se configuran para establecer una comunicación bidireccional entre el UAV y la estación base. Para conseguir un control fiable se ha utiliza el protocolo de comunicación MAVLink. Se ha seleccionado un controlador de vuelo (autopilot) comercial, llamado Pixhawk, que utiliza este mismo sistema para transmisión de la telemetría a la estación base el cual se adapta para conseguir que también interprete las órdenes de control utilizando el mismo protocolo. Se realiza un estudio de su arquitectura software y se describen sus módulos principales de manera que se hace posible la intervención dentro del código fuente para agregar/modificar funcionalidades según lo requiera el proyecto. Se implementa un conjunto de modificaciones que permite sustituir el control remoto de la aeronave basado en un mando RC comercial estándar por un mando digital conectado al ordenador en la estación base, abriendo la posibilidad de comunicación de comandos de vuelo generados automáticamente en la estación base. Además se crea una aplicación para enviar las acciones del operario sobre el control de vuelo desde la estación base.This project involves the creation of a teleoperation system of quadcopter type UAV. Two wireless links are designed for transmitting video signal and data, it is studied a wide range of modules available in the market and it is selected the right set for the initial development phase of the project. The video transmission system consists of two different links which can work together avoiding interferences by using orthogonal polarization each other. Thus, the UAV can be equipped with two video cameras and transmit both signals simultaneously. The data link is implemented by using two XBee modules configured to provide bidirectional communication between the UAV and the base station. MAVLink communication protocol is used to achieve reliable control link. It is selected a commercial autopilot, called Pixhawk, which use MAVLink communication protocol to transmit telemetry to the base station. It is adapted to ensure that the autopilot also interprets control commands using the same protocol. A study of its software architecture is performed and its main modules are described so that intervention is possible within the source code to add or modify functionality as required by the project. It is implemented a set of modifications that allows replacing the aircraft remote control based on a standard commercial RC remote controller by a digital joystick connected to the base station computer. This makes possible sending control commands automatically generated in the base station. Furthermore, a control application is created to send control commands from the base station