Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot

SIRU development. Volume 1: System development

A complete description of the development and initial evaluation of the Strapdown Inertial Reference Unit (SIRU) system is reported. System development documents the system mechanization with the analytic formulation for fault detection and isolation processing structure; the hardware redundancy design and the individual modularity features; the computational structure and facilities; and the initial subsystem evaluation results

Reliable dual-redundant sensor failure detection and identification for the NASA F-8 DFBW aircraft

A technique was developed which provides reliable failure detection and identification (FDI) for a dual redundant subset of the flight control sensors onboard the NASA F-8 digital fly by wire (DFBW) aircraft. The technique was successfully applied to simulated sensor failures on the real time F-8 digital simulator and to sensor failures injected on telemetry data from a test flight of the F-8 DFBW aircraft. For failure identification the technique utilized the analytic redundancy which exists as functional and kinematic relationships among the various quantities being measured by the different control sensor types. The technique can be used not only in a dual redundant sensor system, but also in a more highly redundant system after FDI by conventional voting techniques reduced to two the number of unfailed sensors of a particular type. In addition the technique can be easily extended to the case in which only one sensor of a particular type is available

Orbital Manuvering System Design and Performance For the Magnetosperic Multiscale Constellation

The Magnetospheric Multiscale (MMS) mission, launched on March 13, 2015, is the fourth mission of NASA's Solar Terrestrial Probe program. The MMS mission consists of four identically instrumented observatories that function as a constellation to provide the first definitive study of magnetic reconnection in space. Since it is frequently desirable to isolate electric and magnetic field sensors from stray effects caused by the spacecraft's core-body, the suite of instruments on MMS includes six radial and two axial instrument-booms with deployed lengths ranging from 5-60 meters (see Figure 1). The observatory is spin-stabilized about its positive z-axis with a nominal rate slightly above 3 rev/min (RPM). The spin is also used to maintain tension in the four radial wire-booms. Each observatory's Attitude Control System (ACS) consists of digital sun sensors, star cameras, accelerometers, and mono-propellant hydrazine thrusters-responsible for orbital adjustments, attitude control, and spin adjustments. The sections that follow describe performance requirements, the hardware and algorithms used for 6-DOF estimation, and then similarly for 6-DOF control. The paper concludes with maneuver performance based on both simulated and on-orbit telem

Improving Dynamics Estimations and Low Level Torque Control Through Inertial Sensing

In 1996, professors J. Edward Colgate and Michael Peshkin invented the cobots as robotic equipment safe enough for interacting with human workers. Twenty years later, collaborative robots are highly demanded in the packaging industry, and have already been massively adopted by companies facing issues for meeting customer demands. Meantime, cobots are still making they way into environments where value-added tasks require more complex interactions between robots and human operators. For other applications like a rescue mission in a disaster scenario, robots have to deal with highly dynamic environments and uneven terrains. All these applications require robust, fine and fast control of the interaction forces, specially in the case of locomotion on uneven terrains in an environment where unexpected events can occur. Such interaction forces can only be modulated through the control of joint internal torques in the case of under-actuated systems which is typically the case of mobile robots. For that purpose, an efficient low level joint torque control is one of the critical requirements, and motivated the research presented here. This thesis addresses a thorough model analysis of a typical low level joint actuation sub-system, powered by a Brushless DC motor and suitable for torque control. It then proposes procedure improvements in the identification of model parameters, particularly challenging in the case of coupled joints, in view of improving their control. Along with these procedures, it proposes novel methods for the calibration of inertial sensors, as well as the use of such sensors in the estimation of joint torques

Design, test, and evaluation of three active flutter suppression controllers

Three control law design techniques for flutter suppression are presented. Each technique uses multiple control surfaces and/or sensors. The first method uses traditional tools (such as pole/zero loci and Nyquist diagrams) for producing a controller that has minimal complexity and which is sufficiently robust to handle plant uncertainty. The second procedure uses linear combinations of several accelerometer signals and dynamic compensation to synthesize the model rate of the critical mode for feedback to the distributed control surfaces. The third technique starts with a minimum-energy linear quadratic Gaussian controller, iteratively modifies intensity matrices corresponding to input and output noise, and applies controller order reduction to achieve a low-order, robust controller. The resulting designs were implemented digitally and tested subsonically on the active flexible wing wind-tunnel model in the Langley Transonic Dynamics Tunnel. Only the traditional pole/zero loci design was sufficiently robust to errors in the nominal plant to successfully suppress flutter during the test. The traditional pole/zero loci design provided simultaneous suppression of symmetric and antisymmetric flutter with a 24-percent increase in attainable dynamic pressure. Posttest analyses are shown which illustrate the problems encountered with the other laws

Implementation of a acceleration estimator based compensation scheme to increase load data accuracy for a robotic testing system for CPR-manikins

Laerdal Medical is a producer of Cardiopulmonary Resuscitation (CPR) training manikins, all of which undergo rigorous endurance and accuracy testing. This work proposes an acceleration estimator based compensation scheme for a industrial robot manipulator product testing system with the intention of increasing load data accuracy for the purpose of product review and calibration. As part of the compensation scheme four different acceleration estimators are implemented and compared. Results indicate that the compensation scheme increases the load data accuracy by 1.5 - 6 % of the reference value depending on compression depth and spring rate. However the accuracy goal of 0.4 [kg] is not reached. The work has also uncovered the presence of position error in the robot. Thus, further improvement to the compensation scheme and positional error compensation is required

Virtual Sensor for Kinematic Estimation of Flexible Links in Parallel Robots

The control of flexible link parallel manipulators is still an open area of research, endpoint trajectory tracking being one of the main challenges in this type of robot. The flexibility and deformations of the limbs make the estimation of the Tool Centre Point (TCP) position a challenging one. Authors have proposed different approaches to estimate this deformation and deduce the location of the TCP. However, most of these approaches require expensive measurement systems or the use of high computational cost integration methods. This work presents a novel approach based on a virtual sensor which can not only precisely estimate the deformation of the flexible links in control applications (less than 2% error), but also its derivatives (less than 6% error in velocity and 13% error in acceleration) according to simulation results. The validity of the proposed Virtual Sensor is tested in a Delta Robot, where the position of the TCP is estimated based on the Virtual Sensor measurements with less than a 0.03% of error in comparison with the flexible approach developed in ADAMS Multibody Software.This work was supported in part by the Spanish Ministry of Economy and Competitiveness under grant BES-2013-066142, UPV/EHU's PPG17/56 projects, Spanish Ministry of Economy and Competitiveness' MINECO & FEDER inside DPI-2012-32882 project and the Basque Country Government's (GV/EJ) under PRE-2014-1-152 and BFI-2012-223 grants and under recognized research group IT914-16