Autonomous Visual Servo Robotic Capture of Non-cooperative Target

This doctoral research develops and validates experimentally a vision-based control scheme for the autonomous capture of a non-cooperative target by robotic manipulators for active space debris removal and on-orbit servicing. It is focused on the final capture stage by robotic manipulators after the orbital rendezvous and proximity maneuver being completed. Two challenges have been identified and investigated in this stage: the dynamic estimation of the non-cooperative target and the autonomous visual servo robotic control. First, an integrated algorithm of photogrammetry and extended Kalman filter is proposed for the dynamic estimation of the non-cooperative target because it is unknown in advance. To improve the stability and precision of the algorithm, the extended Kalman filter is enhanced by dynamically correcting the distribution of the process noise of the filter. Second, the concept of incremental kinematic control is proposed to avoid the multiple solutions in solving the inverse kinematics of robotic manipulators. The proposed target motion estimation and visual servo control algorithms are validated experimentally by a custom built visual servo manipulator-target system. Electronic hardware for the robotic manipulator and computer software for the visual servo are custom designed and developed. The experimental results demonstrate the effectiveness and advantages of the proposed vision-based robotic control for the autonomous capture of a non-cooperative target. Furthermore, a preliminary study is conducted for future extension of the robotic control with consideration of flexible joints

Force control of lightweight series elastic systems using enhanced disturbance observers

This paper analyzes the control challenges associated to lightweight series elastic systems in force control applications, showing that a low end-point inertia can lead to high sensitivity to environment uncertainties. Where mainstream force control methods fail, this paper proposes a control methodology to enhance the performance robustness of existing disturbance observers (DOBs). The approach is validated experimentally and successfully compared to basic control solutions and state of the art DOB approaches

Intuitive wireless control of a robotic arm for people living with an upper body disability

Assistive Technologies (ATs) also called extrinsic enablers are useful tools for people living with various disabilities. The key points when designing such useful devices not only concern their intended goal, but also the most suitable human-machine interface (HMI) that should be provided to users. This paper describes the design of a highly intuitive wireless controller for people living with upper body disabilities with a residual or complete control of their neck and their shoulders. Tested with JACO, a six-degree-of-freedom (6-DOF) assistive robotic arm with 3 flexible fingers on its end-effector, the system described in this article is made of low-cost commercial off-the-shelf components and allows a full emulation of JACO's standard controller, a 3 axis joystick with 7 user buttons. To do so, three nine-degree-of-freedom (9-DOF) inertial measurement units (IMUs) are connected to a microcontroller and help measuring the user's head and shoulders position, using a complementary filter approach. The results are then transmitted to a base-station via a 2.4-GHz low-power wireless transceiver and interpreted by the control algorithm running on a PC host. A dedicated software interface allows the user to quickly calibrate the controller, and translates the information into suitable commands for JACO. The proposed controller is thoroughly described, from the electronic design to implemented algorithms and user interfaces. Its performance and future improvements are discussed as well

Non-Linear Robust Observers For Systems With Non-Collocated Sensors And Actuators

Challenges in controlling highly nonlinear systems are not limited to the development of sophisticated control algorithms that are tolerant to significant modeling imprecision and external disturbances. Additional challenges stem from the implementation of the control algorithm such as the availability of the state variables needed for the computation of the control signals, and the adverse effects induced by non-collocated sensors and actuators. The present work investigates the adverse effects of non-collocated sensors and actuators on the phase characteristics of flexible structures and the ensuing implications on the performance of structural controllers. Two closed-loop systems are considered and their phase angle contours have been generated as functions of the normalized sensor location and the excitation frequency. These contours were instrumental in the development of remedial actions for rendering structural controllers immune to the detrimental effects of non-collocated sensors and actuators. Moreover, the current work has focused on providing experimental validation for the robust performances of a self-tuning observer and a sliding mode observer. The observers are designed based on the variable structure systems theory and the self-tuning fuzzy logic scheme. Their robustness and self-tuning characteristics allow one to use an imprecise model of the system and eliminate the need for the extensive tuning associated with a fixed rule-based expert fuzzy inference system. The first phase of the experimental work was conducted in a controlled environment on a flexible spherical robotic manipulator whose natural frequencies are configuration-dependent. Both controllers have yielded accurate estimates of the required state variables in spite of significant modeling imprecision. The observers were also tested under a completely uncontrolled environment, which involves a 16-ft boat operating in open-water under different sea states. Such an experimental work necessitates the development of a supervisory control algorithm to perform PTP tasks, prescribed throttle arm and steering tasks, surge speed and heading tracking tasks, or recovery maneuvers. This system has been implemented herein to perform prescribed throttle arm and steering control tasks based on estimated rather than measured state variables. These experiments served to validate the observers in a completely uncontrolled environment and proved their viability as reliable techniques for providing accurate estimates for the required state variables

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

Human Arm Motion Tracking by Kinect Sensor Using Kalman Filter for Collaborative Robotics

The rising interest in collaborative robotics leads to research solutions in order to increase robot interaction with the environment. The development of methods that permit robots to recognize and track human motion is relevant for safety and collaboration matters. A large quantity of data can be measured in real time by Microsoft Kinect®, a well-known low-cost depth sensor, able to recognize human presence and to provide postural information by extrapolating a skeleton. However, the Kinect sensor tracks motion with relatively low accuracy and jerky behavior. For this reason, the effective use in industrial applications in which the measurement of arm velocity is required can be unsuitable. The present work proposes a filtering method that allows the measurement of more accurate velocity values of human arm, based on row data provided by the Kinect sensor. The estimation of arm motion is achieved by a Kalman filter based on a kinematic model and by the imposition of fixed lengths for the skeleton links detected by the sensor. The development of the method is supported by experimental tests. The achieved results suggest the practical applicability of the developed algorithms

Designing an AR interface to improve trust in Human-Robots collaboration

In a global, e-commerce marketplace, product customisation is driven towards manufacturing flexibility. Conventional caged robots are designed for high volume and low mix production cannot always comply with the increasing low volume and high customisation requirements. In this scenario, the interest in collaborative robots is growing. A critical aspect of Human-Robot Collaboration (HRC) is human trust in robots. This research focuses on increasing the human confidence and trust in robots by designing an Augmented Reality (AR) interface for HRC. The variable affecting the trust involved in HRC have been estimated. These have been utilised for designing the AR-HRC. The proposed design aims to provide situational awareness and spatial dialog. The AR-HRC developed has been tested on 15 participants which have performed a “pick-and-place” task. The results show that the utilisation of AR in the proposed scenario positively affects the human trust in robot. The human-robot collaboration enhanced by AR are more natural and effective. The trust has been measured through an empirical psychometric method also presented in this paper

Protection and fault location schemes suited to large-scale multi-vendor high voltage direct current grids

Recent developments in voltage source converter (VSC) technology have led to an increased interest in high voltage direct current (HVDC) transmission to support the integration of massive amounts of renewable energy sources (RES) and especially, offshore wind energy. VSC-based HVDC grids are considered to be the natural evolution of existing point-to-point links and are expected to be one of the key enabling technologies towards expediting the integration and better utilisation of offshore energy, dealing with the variable nature of RES, and driving efficient energy balance over wide areas and across countries. Despite the technological advancements and the valuable knowledge gained from the operation of the already built multi-terminal systems, there are several outstanding issues that need to be resolved in order to facilitate the deployment of large-scale meshed HVDC grids. HVDC protection is of utmost importance to ensure the necessary reliability and security of HVDC grids, yet very challenging due to the fast nature of development of DC faults and the abrupt changes they cause in currents and voltages that may damage the system components. This situation is further exacerbated in highly meshed networks, where the effects of a DC fault on a single component (e.g. DC cable) can quickly propagate across the entire HVDC grid. To mitigate the effect of DC faults in large-scale meshed HVDC grids, fast and fully selective approaches using dedicated DC circuit breaker and protection relays are required. As the speed of DC fault isolation is one order of magnitude faster than typical AC protection (i.e. less than 10 ms), there is a need for the development of innovative approaches to system protection, including the design and implementation of more advanced protection algorithms. Moreover, in a multi-vendor environment (in which different or the same type of equipment is supplied by various manufacturers), the impact of the grid elements on the DC fault signature may differ considerably from case to case, thus increasing the complexity of designing reliable protection algorithms for HVDC grids. Consequently, there is a need for a more fundamental approach to the design and development of protection algorithms that will enable their general applicability. Furthermore, following successful fault clearance, the next step is to pinpoint promptly the exact location of the fault along the transmission medium in an effort to expedite inspection and repair time, reduce power outage time and elevate the total availability of the HVDC grid. Successful fault location becomes increasingly challenging in HVDC grids due to the short time windows between fault inception and fault clearance that limit the available fault data records that may be utilised for the execution of fault location methods. This thesis works towards the development of protection and fault location solutions, designed specifically for application in large-scale multi-vendor HVDC grids. First, a methodology is developed for the design of travelling wave based non-unit protection algorithms that can be easily configured for any grid topology and parameters. Second, using this methodology, a non-unit protection algorithm based on wavelet transform is developed that ensures fast, discriminative and enhanced protection performance. Besides offline simulations, the efficacy of the wavelet transform based algorithm is also demonstrated by means of real-time simulation, thereby removing key technical barriers that have impeded the use of wavelet transform in practical protection applications. Third, in an effort to reinforce the technical and economic feasibility of future HVDC grids, a thorough fault management strategy is presented for systems that employ efficient modular multilevel converters with partial fault tolerant capability. Finally, a fault location scheme is developed for accurately estimating the fault location in HVDC grids that are characterised by short post-fault data windows due to the utilisation of fast acting protection systems.Recent developments in voltage source converter (VSC) technology have led to an increased interest in high voltage direct current (HVDC) transmission to support the integration of massive amounts of renewable energy sources (RES) and especially, offshore wind energy. VSC-based HVDC grids are considered to be the natural evolution of existing point-to-point links and are expected to be one of the key enabling technologies towards expediting the integration and better utilisation of offshore energy, dealing with the variable nature of RES, and driving efficient energy balance over wide areas and across countries. Despite the technological advancements and the valuable knowledge gained from the operation of the already built multi-terminal systems, there are several outstanding issues that need to be resolved in order to facilitate the deployment of large-scale meshed HVDC grids. HVDC protection is of utmost importance to ensure the necessary reliability and security of HVDC grids, yet very challenging due to the fast nature of development of DC faults and the abrupt changes they cause in currents and voltages that may damage the system components. This situation is further exacerbated in highly meshed networks, where the effects of a DC fault on a single component (e.g. DC cable) can quickly propagate across the entire HVDC grid. To mitigate the effect of DC faults in large-scale meshed HVDC grids, fast and fully selective approaches using dedicated DC circuit breaker and protection relays are required. As the speed of DC fault isolation is one order of magnitude faster than typical AC protection (i.e. less than 10 ms), there is a need for the development of innovative approaches to system protection, including the design and implementation of more advanced protection algorithms. Moreover, in a multi-vendor environment (in which different or the same type of equipment is supplied by various manufacturers), the impact of the grid elements on the DC fault signature may differ considerably from case to case, thus increasing the complexity of designing reliable protection algorithms for HVDC grids. Consequently, there is a need for a more fundamental approach to the design and development of protection algorithms that will enable their general applicability. Furthermore, following successful fault clearance, the next step is to pinpoint promptly the exact location of the fault along the transmission medium in an effort to expedite inspection and repair time, reduce power outage time and elevate the total availability of the HVDC grid. Successful fault location becomes increasingly challenging in HVDC grids due to the short time windows between fault inception and fault clearance that limit the available fault data records that may be utilised for the execution of fault location methods. This thesis works towards the development of protection and fault location solutions, designed specifically for application in large-scale multi-vendor HVDC grids. First, a methodology is developed for the design of travelling wave based non-unit protection algorithms that can be easily configured for any grid topology and parameters. Second, using this methodology, a non-unit protection algorithm based on wavelet transform is developed that ensures fast, discriminative and enhanced protection performance. Besides offline simulations, the efficacy of the wavelet transform based algorithm is also demonstrated by means of real-time simulation, thereby removing key technical barriers that have impeded the use of wavelet transform in practical protection applications. Third, in an effort to reinforce the technical and economic feasibility of future HVDC grids, a thorough fault management strategy is presented for systems that employ efficient modular multilevel converters with partial fault tolerant capability. Finally, a fault location scheme is developed for accurately estimating the fault location in HVDC grids that are characterised by short post-fault data windows due to the utilisation of fast acting protection systems

Modeling and Control of Flexible Link Manipulators

Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.publishedVersio