MODELLING AND CONTROL OF MULTI-FINGERED ROBOT HAND USING INTELLIGENT TECHNIQUES

Research and development of robust multi-fingered robot hand (MFRH) have been going on for more than three decades. Yet few can be found in an industrial application. The difficulties stem from many factors, one of which is that the lack of general and effective control techniques for the manipulation of robot hand. In this research, a MFRH with five fingers has been proposed with intelligent control algorithms. Initially, mathematical modeling for the proposed MFRH has been derived to find the Forward Kinematic, Inverse Kinematic, Jacobian, Dynamics and the plant model. Thereafter, simulation of the MFRH using PID controller, Fuzzy Logic Controller, Fuzzy-PID controller and PID-PSO controller has been carried out to gauge the system performance based parameters such rise time, settling time and percent overshoot

Intelligent strategies for mobile robotics in laboratory automation

In this thesis a new intelligent framework is presented for the mobile robots in laboratory automation, which includes: a new multi-floor indoor navigation method is presented and an intelligent multi-floor path planning is proposed; a new signal filtering method is presented for the robots to forecast their indoor coordinates; a new human feature based strategy is proposed for the robot-human smart collision avoidance; a new robot power forecasting method is proposed to decide a distributed transportation task; a new blind approach is presented for the arm manipulations for the robots

UltraSwarm: A Further Step Towards a Flock of Miniature Helicopters

We describe further progress towards the development of a MAV (micro aerial vehicle) designed as an enabling tool to investigate aerial flocking. Our research focuses on the use of low cost off the shelf vehicles and sensors to enable fast prototyping and to reduce development costs. Details on the design of the embedded electronics and the modification of the chosen toy helicopter are presented, and the technique used for state estimation is described. The fusion of inertial data through an unscented Kalman filter is used to estimate the helicopter’s state, and this forms the main input to the control system. Since no detailed dynamic model of the helicopter in use is available, a method is proposed for automated system identification, and for subsequent controller design based on artificial evolution. Preliminary results obtained with a dynamic simulator of a helicopter are reported, along with some encouraging results for tackling the problem of flocking

An analysis on controlling humanoid robot arm using Robot Operating System (ROS)

Humanoid robots are extensively discussed in modern days. The movement task and manipulation of Humanoid Robots is examined based on mobility of platforms and control of the arm. This project describes a robotic arm that is analogous to an arm of a human being. Some important parameters to be considered are reachability, stability and manipulability. This thesis aims at adapting a humanoid robot arm for performing movement operation that can be used for various purposes. The proposed robot arm has 3 motors on the left arm and 3 motors on the right arm thereby constituting a total of 6 motors. This operation can be achieved by the use of sensor like ultrasonic sensor. Here Beaglebone Black, an open source linux based controller board is used. The Beaglebone Black acts as the main controller for the entire system. A research is also being made to implement the robotic arm using Robot Operating System (ROS) platform. ROS is preferred since it is modular, simple and easy to use tools for development, it provides good hardware support, lots of algorithms are implemented together as package, etc

Medical robots for MRI guided diagnosis and therapy

Magnetic Resonance Imaging (MRI) provides the capability of imaging tissue with fine resolution and superior soft tissue contrast, when compared with conventional ultrasound and CT imaging, which makes it an important tool for clinicians to perform more accurate diagnosis and image guided therapy. Medical robotic devices combining the high resolution anatomical images with real-time navigation, are ideal for precise and repeatable interventions. Despite these advantages, the MR environment imposes constraints on mechatronic devices operating within it. This thesis presents a study on the design and development of robotic systems for particular MR interventions, in which the issue of testing the MR compatibility of mechatronic components, actuation control, kinematics and workspace analysis, and mechanical and electrical design of the robot have been investigated. Two types of robotic systems have therefore been developed and evaluated along the above aspects. (i) A device for MR guided transrectal prostate biopsy: The system was designed from components which are proven to be MR compatible, actuated by pneumatic motors and ultrasonic motors, and tracked by optical position sensors and ducial markers. Clinical trials have been performed with the device on three patients, and the results reported have demonstrated its capability to perform needle positioning under MR guidance, with a procedure time of around 40mins and with no compromised image quality, which achieved our system speci cations. (ii) Limb positioning devices to facilitate the magic angle effect for diagnosis of tendinous injuries: Two systems were designed particularly for lower and upper limb positioning, which are actuated and tracked by the similar methods as the first device. A group of volunteers were recruited to conduct tests to verify the functionality of the systems. The results demonstrate the clear enhancement of the image quality with an increase in signal intensity up to 24 times in the tendon tissue caused by the magic angle effect, showing the feasibility of the proposed devices to be applied in clinical diagnosis

Actuators and sensors for application in agricultural robots: A review

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future

Pjezorobotų trajektorijų valdymas nanopalydovų stabilizavimui

Rapid industrial advancement requires novel ideas, new scientific approaches and effective technologies that would ensure quality and precision. Application of piezoelectric actuators in robotics opens many possibilities to create systems with extreme precision and control. A very important step in the development of autonomous robots is the formation of motion trajectories. Classical interpolation methods used for formation of the trajectories are suitable only when robots have wheels, legs or other parts for motion transmission. Piezorobots that are analyzed in this dissertation have no additional components that create motion, only contact points with the static plane. Therefore, traditional motion formation methods are not suitable and a problem arises how to define motion trajectory of such device. The aim of this work is to create a trajectory control algorithm of multi-degrees-of-freedom piezorobot used for nanosatellite stabilization. In order to achieve the objective, the following tasks had to be solved: to analyze constructions of precise piezorobots, their operating principles and motion formation methods; to analyze stabilization problems of satellites and application of multi-degrees-of-freedom piezorobots for nanosatellite stabilization; to create piezorobots’ motion formation algorithms according to electrode excitation schemes, to perform an experimental research; to determine quantitative characteristics of the constructed piezorobots and their motion trajectories. The introduction describes the importance and novelty of this thesis, goals of this work, its practical value and defended statements. The first chapter analyses the principals of ultrasonic devices, gives a thorough review of constructions of ultrasonic devices with multi-degrees-of-freedom. The second chapter provides a review of satellite stabilization principles and how multi-degrees-of-freedom piezorobots can be applied for nanosatellite stabilization. Motion formation methods for ultrasonic devices with multi-degrees-of-freedom are presented. The third chapter presents the detailed analysis of different piezorobots. In the fourth chapter experimental results are provided. Trajectory planning of piezorobot is shown, results are compared to numerical calculations performed in the third chapter. The conclusions about applicability of piezorobots’ motion formation algorithms according to electrode excitation schemes are given. Seven articles focusing on the subject of the dissertation have been published, two presentations on the subject have been presented in conferences at international level. The research for the dissertation has been funded by the Lithuanian State Science and Studies Foundation: European Regional Development Fund, Project No. DOTSUT-234 and Research Council of Lithuania, Project No. MIP-084/2015.Dissertatio

Real-Time Inverse Dynamic Deep Neural Network Tracking Control for Delta Robot Based on a COVID-19 Optimization

This paper presents a new technique to design an inverse dynamic model for a delta robot experimental setup to obtain an accurate trajectory. The input/output data were collected using an NI DAQ card where the input is the random angles profile for the three-axis and the output is the corresponding measured torques. The inverse dynamic model was developed based on the deep neural network (NN) and the new COVID-19 optimization to find the optimal initial weights and bias values of the NN model. Due to the system uncertainty and nonlinearity, the inverse dynamic model is not enough to track accurately the preselected profile. So, the PD compensator is used to absorb the error deviation of the end effector. The experimental results show that the proposed inverse dynamic deep NN with PD compensator achieves good performance and high tracking accuracy. The suggested control was examined using two different methods. The spiral path is the first, with a root mean square error of 0.00258 m, while the parabola path is the second, with a root mean square error of 0.00152 m