Force/Position Hybrid Control of 6PUS-UPU Redundant Driven Parallel Manipulator Based on 2-DOF Internal Model Control

To improve control performance of parallel manipulator, servo control is optimized according to 2-DOF control with Internal Model Control. Position loop of the controller is redesigned based on the original current loop and speed loop. The hybrid force/position control strategy on the basis of cross-coupling is proposed. With mechatronic cosimulation system, it is proved that the force/position hybrid control on the basis of 2-DOF Internal Model Control has better stability and position precision compared with the traditional PID control. The control precision and stability of the parallel manipulator are improved effectively in actual experiment. Two types of compliance operation including peg in hole and surface tracking are realized in 6PUS-UPU parallel manipulator and both have good applicable effect

Haptic-Enabled Handheld Mobile Robots: Design and Analysis

The Cellulo robots are small tangible robots that are designed to represent virtual interactive point-like objects that reside on a plane within carefully designed learning activities. In the context of these activities, our robots not only display autonomous motion and act as tangible interfaces, but are also usable as haptic devices in order to exploit, for instance, kinesthetic learning. In this article, we present the design and analysis of the haptic interaction module of the Cellulo robots. We first detail our hardware and controller design that is low-cost and versatile. Then, we describe the task-based experimental procedure to evaluate the robot's haptic abilities. We show that our robot is usable in most of the tested tasks and extract perceptive and manipulative guidelines for the design of haptic elements to be integrated in future learning activities. We conclude with limitations of the system and future work

Assistive control for non-contact machining of random shaped contours

Recent achievements in robotics and automation technology has opened the door towards different machining methodologies based on material removal. Considering the non force feedback nature of non-contact machining methods, careful attention on motion control design is a primary requirement for successful achievement of precise cutting both in machining and in surgery processes. This thesis is concerned with the design of pre-processing methods and motion control techniques to provide both automated and human-assistive non-contact machining of random and complex shaped contours. In that sense, the first part of the thesis focuses on extraction of contours and generation of reference trajectories or constraints for the machining system. Based on generated trajectories, two different control schemes are utilized for high precision automated machining. In the first scheme, preview control is adopted for enhancing the tracking performance. In the second scheme, control action is generated based on direct computation of contouring error in the operational space by introducing a new coordinate frame moving with the reference contour. Further, non-contact machining is extended for realization in a master/slave telerobotic framework to enable manual remote cutting by a human operator. With the proposed approach, the human operator (i.e. a surgeon) is limited to conduct motion within a desired virtual constraint and is equipped with the ability of adjusting the cutting depth over a that contour providing advantage for laser surgery applications. The proposed framework is experimentally tested and results of the experiments prove the applicability of proposed motion control schemes and show the validity of contributions made in the context of thesis

Design, Modeling and Control of Micro-scale and Meso-scale Tendon-Driven Surgical Robots

Manual manipulation of passive surgical tools is time consuming with uncertain results in cases of navigating tortuous anatomy, avoiding critical anatomical landmarks, and reaching targets not located in the linear range of these tools. For example, in many cardiovascular procedures, manual navigation of a micro-scale passive guidewire results in increased procedure times and radiation exposure. This thesis introduces the design of two steerable guidewires: 1) A two degree-of-freedom (2-DoF) robotic guidewire with orthogonally oriented joints to access points in a three dimensional workspace, and 2) a micro-scale coaxially aligned steerable (COAST) guidewire robot that demonstrates variable and independently controlled bending length and curvature of the distal end. The 2-DoF guidewire features two micromachined joints from a tube of superelastic nitinol of outer diameter 0.78 mm. Each joint is actuated with two nitinol tendons. The joints that are used in this robot are called bidirectional asymmetric notch (BAN) joints, and the advantages of these joints are explored and analyzed. The design of the COAST robotic guidewire involves three coaxially aligned tubes with a single tendon running centrally through the length of the robot. The outer tubes are made from micromachined nitinol allowing for tendon-driven bending of the robot at variable bending curvatures, while an inner stainless steel tube controls the bending length of the robot. By varying the lengths of the tubes as well as the tendon, and by insertion and retraction of the entire assembly, various joint lengths and curvatures may be achieved. Kinematic and static models, a compact actuation system, and a controller for this robot are presented. The capability of the robot to accurately navigate through phantom anatomical bifurcations and tortuous angles is also demonstrated in three dimensional phantom vasculature. At the meso-scale, manual navigation of passive pediatric neuroendoscopes for endoscopic third ventriculostomy may not reach target locations in the patient's ventricle. This work introduces the design, analysis and control of a meso-scale two degree-of-freedom robotic bipolar electrocautery tool that increases the workspace of the neurosurgeon. A static model is proposed for the robot joints that avoids problems arising from pure kinematic control. Using this model, a control system is developed that comprises of a disturbance observer to provide precise force control and compensate for joint hysteresis. A handheld controller is developed and demonstrated in this thesis. To allow the clinician to estimate the shape of the steerable tools within the anatomy for both micro-scale and meso-scale tools, a miniature tendon force sensor and a high deflection shape sensor are proposed and demonstrated. The force sensor features a compact design consisting of a single LED, dual-phototransistor, and a dual-screen arrangement to increase the linear range of sensor output and compensate for external disturbances, thereby allowing force measurement of up to 21 N with 99.58 % accuracy. The shape sensor uses fiber Bragg grating based optical cable mounted on a micromachined tube and is capable of measuring curvatures as high as 145 /m. These sensors were incorporated and tested in the guidewire and the neuroendoscope tool robots and can provide robust feedback for closed-loop control of these devices in the future.Ph.D

FPGAs in Industrial Control Applications

The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs

Advances in Human Robot Interaction for Cloud Robotics applications

In this thesis are analyzed different and innovative techniques for Human Robot Interaction. The focus of this thesis is on the interaction with flying robots. The first part is a preliminary description of the state of the art interactions techniques. Then the first project is Fly4SmartCity, where it is analyzed the interaction between humans (the citizen and the operator) and drones mediated by a cloud robotics platform. Then there is an application of the sliding autonomy paradigm and the analysis of different degrees of autonomy supported by a cloud robotics platform. The last part is dedicated to the most innovative technique for human-drone interaction in the User’s Flying Organizer project (UFO project). This project wants to develop a flying robot able to project information into the environment exploiting concepts of Spatial Augmented Realit

Doctor of Philosophy

dissertationWhen interacting with objects, humans utilize their sense of touch to provide information about the object and surroundings. However, in video games, virtual reality, and training exercises, humans do not always have information available through the sense of touch. Several types of haptic feedback devices have been created to provide touch information in these scenarios. This dissertation describes the use of tactile skin stretch feedback to provide cues that convey direction information to a user. The direction cues can be used to guide a user or provide information about the environment. The tactile skin stretch feedback devices described herein provide feedback directly to the hands, just as in many real life interactions involving the sense of touch. The devices utilize a moving tactor (actuated skin contact surface, also called a contactor) and surrounding material to give the user a sense of the relative motion. Several game controller prototypes with skin stretch feedback embedded into the device to interface with the fingers were constructed. Experiments were conducted to evaluate user performance in moving the joysticks to match the direction of the stimulus. These experiments investigated stimulus masking effects with both skin stretch feedback and vibrotactile feedback. A controller with feedback on the thumb joysticks was found to have higher user accuracy. Next, precision grip and power grip skin stretch feedback devices were created to investigate cues to convey motion in a three-dimensional space. Experiments were conducted to compare the two devices and to explore user accuracy in identifying different direction cue types. The precision grip device was found to be superior in communicating direction cues to users in four degrees of freedom. Finally, closed-loop control was implemented to guide users to a specific location and orientation within a three-dimensional space. Experiments were conducted to improve controller feedback which in turn improved user performance. Experiments were also conducted to investigate the feasibility of providing multiple cues in succession, in order to guide a user with multiple motions of the hand. It was found that users can successfully reach multiple target locations and orientations in succession

Intelligent active torque control for vibration reduction of a sprayer boom suspension system

The most usual way of protecting crop from diseases is by using chemical method whereby mixture of chemicals and water are sprayed onto crop via nozzles. These nozzles are located consistently along a boom structure oriented perpendicular to the direction of motion to cover large areas. The most important factor on spray distribution pattern is spray boom vibration. Thus, suspension control aims to attenuate the unwanted vibration and should provide improvements in term of distribution uniformity. In this study, a combination of passive and active suspension was considered to create superior performance. A passive suspension was employed to control undesired vertical motion of sprayer boom structure while the roll movement of spray boom was reduced via active suspension. The active suspension system of sprayer was implemented by applying robust active torque control (ATC) scheme that integrates artificial intelligence (AI) methods plus another feedback control technique utilizing proportional-integral-derivative (PID) control. The proposed control system basically comprises of two feedback control loops; an innermost loop for compensation of the disturbances using ATC strategy and an outermost loop for the computation of the desired torque for the actuator using a PID controller. Two AI methods employing artificial neural network (ANN) and iterative learning (IL) were proposed and utilized to compute the estimated inertial parameter of the system through the ATC loop. The research proposes two main control schemes; the first is a combination of ATC and ANN (ATCANN) while the other is ATC and IL (ATCAIL). The suspension system was first modeled and a number of farmland terrains were simulated as the main disturbance components to verify the robustness of the system and sprayer boom dynamic performance related to distribution uniformity. The simulation results both in frequency and time domains show the effectiveness of the proposed ATC schemes in reducing the disturbances and other loading conditions. The control schemes were further implemented experimentally on a developed laboratory spray boom suspension test rig

Event and Time-Triggered Control Module Layers for Individual Robot Control Architectures of Unmanned Agricultural Ground Vehicles

Automation in the agriculture sector has increased to an extent where the accompanying methods for unmanned field management are becoming more economically viable. This manifests in the industry’s recent presentation of conceptual cab-less machines that perform all field operations under the high-level task control of a single remote operator. A dramatic change in the overall workflow for field tasks that historically assumed the presence of a human in the immediate vicinity of the work is predicted. This shift in the entire approach to farm machinery work provides producers increased control and productivity over high-level tasks and less distraction from operating individual machine actuators and implements. The final implication is decreased mechanical complexity of the cab-less field machines from their manned counter types. An Unmanned Agricultural Ground Vehicle (UAGV) electric platform received a portable control module layer (CML) which was modular and able to accept higher-level mission commands while returning system states to high-level tasks. The simplicity of this system was shown by its entire implementation running on microcontrollers networked on a Time-Triggered Controller Area Network (TTCAN) bus. A basic form of user input and output was added to the system to demonstrate a simple instance of sub-system integration. In this work, all major levels of design and implementation are examined in detail, revealing the ‘why’ and ‘how’ of each subsystem. System design philosophy is highlighted from the beginning. A state-space feedback steering controller was implemented on the machine utilizing a basic steering model found in literature. Finally, system performance is evaluated from the perspectives of a number of disciplines including: embedded systems software design, control systems, and robot control architecture. Recommendations for formalized UAGV system modeling, estimation, and control are discussed for the continuation of research in simplified low-cost machines for in-field task automation. Additional recommendations for future time-triggered CML experiments in bus robustness and redundancy are discussed. The work presented is foundational in the shift from event-triggered communications towards time-triggered CMLs for unmanned agricultural machinery and is a front-to-back demonstration of time-triggered design. Advisor: Santosh K. Pitl

Improving the safety and efficiency of rail yard operations using robotics

textSignificant efforts have been expended by the railroad industry to make operations safer and more efficient through the intelligent use of sensor data. This work proposes to take the technology one step further to use this data for the control of physical systems designed to automate hazardous railroad operations, particularly those that require humans to interact with moving trains. To accomplish this, application specific requirements must be established to design self-contained machine vision and robotic solutions to eliminate the risks associated with existing manual operations. Present-day rail yard operations have been identified as good candidates to begin development. Manual uncoupling, in particular, of rolling stock in classification yards has been investigated. To automate this process, an intelligent robotic system must be able to detect, track, approach, contact, and manipulate constrained objects on equipment in motion. This work presents multiple prototypes capable of autonomously uncoupling full-scale freight cars using feedback from its surrounding environment. Geometric image processing algorithms and machine learning techniques were implemented to accurately identify cylindrical objects in point clouds generated in real-vi time. Unique methods fusing velocity and vision data were developed to synchronize a pair of moving rigid bodies in real-time. Multiple custom end-effectors with in-built compliance and fault tolerance were designed, fabricated, and tested for grasping and manipulating cylindrical objects. Finally, an event-driven robotic control application was developed to safely and reliably uncouple freight cars using data from 3D cameras, velocity sensors, force/torque transducers, and intelligent end-effector tooling. Experimental results in a lab setting confirm that modern robotic and sensing hardware can be used to reliably separate pairs of rolling stock up to two miles per hour. Additionally, subcomponents of the autonomous pin-pulling system (APPS) were designed to be modular to the point where they could be used to automate other hazardous, labor-intensive tasks found in U.S. classification yards. Overall, this work supports the deployment of autonomous robotic systems in semi-unstructured yard environments to increase the safety and efficiency of rail operations.Mechanical Engineerin