Intuitive Teleoperation of an Intelligent Robotic System Using Low-Cost 6-DOF Motion Capture

There is currently a wide variety of six degree-of-freedom (6-DOF) motion capture technologies available. However, these systems tend to be very expensive and thus cost prohibitive. A software system was developed to provide 6-DOF motion capture using the Nintendo Wii remote’s (wiimote) sensors, an infrared beacon, and a novel hierarchical linear-quaternion Kalman filter. The software is made freely available, and the hardware costs less than one hundred dollars. Using this motion capture software, a robotic control system was developed to teleoperate a 6-DOF robotic manipulator via the operator’s natural hand movements. The teleoperation system requires calibration of the wiimote’s infrared cameras to obtain an estimate of the wiimote’s 6-DOF pose. However, since the raw images from the wiimote’s infrared camera are not available, a novel camera-calibration method was developed to obtain the camera’s intrinsic parameters, which are used to obtain a low-accuracy estimate of the 6-DOF pose. By fusing the low-accuracy estimate of 6-DOF pose with accelerometer and gyroscope measurements, an accurate estimation of 6-DOF pose is obtained for teleoperation. Preliminary testing suggests that the motion capture system has an accuracy of less than a millimetre in position and less than one degree in attitude. Furthermore, whole-system tests demonstrate that the teleoperation system is capable of controlling the end effector of a robotic manipulator to match the pose of the wiimote. Since this system can provide 6-DOF motion capture at a fraction of the cost of traditional methods, it has wide applicability in the field of robotics and as a 6-DOF human input device to control 3D virtual computer environments

Study of the development of automatic control systems for autonomous exploration robots

El projecte consisteix en la recerca, disseny i possible programació de sistemes de control per tal de conferir al rover d’una certa autonomia i poder controlar-lo en situacions on el control en temps real no sigui factible o desitjat. Aquest estudi inclou la recerca i disseny de sistemes sensorials, sistemes de detecció d’obstacles i sistemes d’optimització de ruta, tant com l’estudi de les actuacions necessàries per a seguir aquesta ruta.This thesis explores the necessities of autonomous exploration rovers within the context of a high latency communications link and proposes a program architecture made up of different modules which takes these necessities into account. A MATLAB simulator is designed and implemented to test the proposed software architecture and to verify the correct behaviour of the proposed algorithms within each module. Finally, these modules are implemented in C++ and tested for verification with a real rover

Design and implementation of resilient attitude estimation algorithms for aerospace applications

Satellite attitude estimation is a critical component of satellite attitude determination and control systems, relying on highly accurate sensors such as IMUs, star trackers, and sun sensors. However, the complex space environment can cause sensor performance degradation or even failure. To address this issue, FDIR systems are necessary. This thesis presents a novel approach to satellite attitude estimation that utilizes an InertialNavigation System (INS) to achieve high accuracy with the low computational load. The algorithm is based on a two-layer Kalman filter, which incorporates the quaternion estimator(QUEST) algorithm, FQA, Linear interpolation (LERP)algorithms, and KF. Moreover, the thesis proposes an FDIR system for the INS that can detect and isolate faults and recover the system safely. This system includes two-layer fault detection with isolation and two-layered recovery, which utilizes an Adaptive Unscented Kalman Filter (AUKF), QUEST algorithm, residual generators, Radial Basis Function (RBF) neural networks, and an adaptive complementary filter (ACF). These two fault detection layers aim to isolate and identify faults while decreasing the rate of false alarms. An FPGA-based FDIR system is also designed and implemented to reduce latency while maintaining normal resource consumption in this thesis. Finally, a Fault Tolerance Federated Kalman Filter (FTFKF) is proposed to fuse the output from INS and the CNS to achieve high precision and robust attitude estimation.The findings of this study provide a solid foundation for the development of FDIR systems for various applications such as robotics, autonomous vehicles, and unmanned aerial vehicles, particularly for satellite attitude estimation. The proposed INS-based approach with the FDIR system has demonstrated high accuracy, fault tolerance, and low computational load, making it a promising solution for satellite attitude estimation in harsh space environment

Assessment of Global Orientation Estimation Using Redundant Inertial and Magnetic Sensors

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Inertial Motion Tracking for Inserting Humans into a Networked Synthetic Environment

Inertial/Magnetic tracking is based on the use of sensors containing three orthogonally mounted angular rate sensors, three orthogonal linear accelerometers and three orthogonal magnetometers to determine independently the orientation of each link of an articulated rigid body. Inertial/magnetic orientation tracking could be applied to a broad range of problems which require real-time tracking of an articulated structure without being continuously dependent upon an artificially generated source. This research focuses on the goal of developing and demonstrating wireless full body tracking using MARG sensor modules.U.S. Army Research OfficeW911NF-04-1-030

Embedded avionics with Kalman state estimation for a novel micro-scale unmanned aerial vehicle

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis. "June 2013."Includes bibliographical references (pages 107-109).An inertial navigation system leveraging Kalman estimation techniques and quaternion dynamics is developed for deployment to a micro-scale unmanned aerial vehicle (UAV). The capabilities, limitations, and requirements of existing navigation solutions motivate the need for an integrated solution that can be readily applied to small embedded systems and still provide reasonably accurate results. Methods to calibrate and compensate systemic inaccuracies in microelectromechanical systems (MEMS) sensors, commonly used in micro-scale UAV applications, are also developed. The problems associated with attitude determination and system localization are analyzed in isolation with incremental simulation and field testing. Performance is evaluated against commercially available inertial navigation system solutions. The result is a capable navigation system that, by its structure, trades a small measure of accuracy in order to be easily adapted to the embedded computing constraints of unmanned vehicles in the micro-scale.by Theodore Tzanetos.M. Eng