Robotics and Mechatronics

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    A Chaotic Neural Network as Motor Path Generator for Mobile Robotics
    (IEEE International Conference on Robotics and Biomimetics, 2014) Folgheraiter, Michele; Gini, Giuseppina
    This work aims at developing a motor path generator for applications in mobile robotics based on a chaotic neural network. The computational paradigm inspired by the neural structure of microcircuits located in the human prefrontal cortex is adapted to work in real-time and used to generate the joints trajectories of a lightweight quadruped robot. The recurrent neural network was implemented in Matlab and a software framework was developed to test the performances of the system with the robot dynamic model. Preliminary results demonstrate the capability of the neural controller to learn period signals in a short period of time allowing adaptation during the robot operation
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    A combined B-Spline-Neural-Network and ARX Model for Online Identi cation of Nonlinear Dynamic Actuation Systems
    (Neurocomputing, 2016) Folgheraiter, Michele
    This paper presents a block oriented nonlinear dynamic model suitable for online identi cation.The model has the well known Hammerstein architecture where as a novelty the nonlinear static part is represented by a B-spline neural network (BSNN), and the linear static one is formalized by an auto regressive exogenous model (ARX). The model is suitable as a feed-forward control module in combination with a classical feedback controller to regulate velocity and position of pneumatic and hydraulic actuation systems which present non stationary nonlinear dynamics. The adaptation of both the linear and nonlinear parts is taking place simultaneously on a patterby- patter basis by applying a combination of error-driven learning rules and the recursive least squares method. This allows to decrease the amount of computation needed to identify the model's parameters and therefore makes the technique suitable for real time applications. The model was tested with a silver box benchmark and results show that the parameters are converging to a stable value after 1500 samples, equivalent to 7.5s of running time. The comparison with a pure ARX and BSNN model indicates a substantial improvement in terms of the RMS error, while the comparison with alternative non linear dynamic models like the NNOE and NNARX, having the same number of parameters but greater computational complexity, shows comparable performances.
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    A Multi-Modal haptic interface for Virtual Reality and Robotics
    (Journal of Intelligent and Robotic Systems, 2008-08) Folgheraiter, Michele; Gini, Giuseppina; Vercesi, Dario
    In this paper we present an innovative haptic device that combines the electro-tactile stimulation with the force and visual feedbacks in order to improve the perception of a virtual world. We discuss about the sensation evoked in a user by the haptic, force, and visual interface provided by this device, implemented as a special glove, equipped with sensors and actua- tors connected to a PC. The techniques used to recreate tactile and kines- thetic sensations are based on an innovative use of cutaneous stimulation integrated with actuators and 3D modelling techniques. We discuss about the specificity of haptic interfaces, their controllers, their open problems. We present results about generating the sensation of touching virtual ob- jects with our device. Experiments show also that, using a multi-modal sensorial pattern of stimulation, the subject perceives more realistically the virtual object. We discuss about possible use of the same technique as a way to interface intelligent robots.
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    A Neuromorphic Motion Controller for a Biped Robot
    (Human Performance and Robotics, Satellite Workshop of IEEE Humanoid 2016, 2016) Folgheraiter, Michele; Keldibek, Amina; Aubakir, Bauyrzhan; Salakchinov, Shyngys; Gini, Giuseppina; Mauro Franchi, Alessio
    Here we propose a neuromorphic control system for a medium size humanoid robot under development in the Robotics and Mechatronics Department at Nazarbayev University and in cooperation with Politecnico di Milano.
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    A Nonlinear Sliding Mode Controller for IPMSM Drives with an Adaptive Gain Tuning Rule
    (2015) Jung, Jin-Woo; Dang, Dong Quang; Vu, Nga Thi-Thuy; Justo, Jackson John; Do, Ton Duc; Choi, Han Ho; Kim, Tae Heoung
    This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC method
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    Actuation Design Methodology for Haptic Interfaces and Rehabilitation Systems
    (IEEE 8th International Conference on Application of Information and Communication Technologies, 2014) Folgheraiter, Michele
    This paper introduces a methodology and a software framework intended to optimize and speed up the design process of a haptic interface or a rehabilitation system. Starting from an initial mechanical design the procedure allows to export the kinematic and dynamic properties of the robotic system in a simulation environment. The software receives as additional input the Cartesian or joints trajectories and generates as output the required torques at the joints. From the recorded measurements the program extracts the torque ranges necessary to choose a suitable actuation system for the robot. The possibility to run the simulation in batch modality allows also to define different optimization techniques that may be used to reduce the overall system weight or increase its payload
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    Adaptive PID Speed Control Design for Permanent Magnet Synchronous Motor Drives
    (2014) Jung, Jin-Woo; Leu, Viet Quoc; Do, Ton Duc; Kim, Eun-Kyung; Choi, Han Ho; Leu, Viet Quoc
    This paper proposes an adaptive proportionalintegralderivative (PID) speed control scheme for permanent magnet synchronous motor (PMSM) drives. The proposed controller consists of three control terms: a decoupling term, a PID term, and a supervisory term. The first control term is employed to compensate for the nonlinear factors, the second term is made to automatically adjust the control gains, and the third one is designed to guarantee the system stability. Different from the offline-tuning PID controllers, the proposed adaptive controller includes adaptive tuning laws to online adjust the control gains based on the gradient descent method. Thus, it can adaptively deal with any system parameter uncertainties in reality. The proposed scheme is not only simple and easy to implement, but also it guarantees an accurate and fast speed tracking. It is proven that the control system is asymptotically stable. To confirm the effectiveness of the proposed algorithm, the comparative experiments between the proposed adaptive PID controller and the conventional PID controller are performed on the PMSM drive. Finally, it is validated that the proposed design scheme accomplishes the superior control performance (faster transient response and smaller steady-state error) compared to the conventional PID method in the presence of parameter uncertainties
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    ADVANCED STEPS IN BIPED ROBOTICS: INNOVATIVE DESIGN AND INTUITIVE CONTROL THROUGH SPRING-DAMPER ACTUATOR
    (4th IEEE/RAS International Conference on Humanoid Robots, 2004) Scarfogliero, Umberto; Folgheraiter, Michele; Gini, Giuseppina
    This paper focuses on the study and design of an anthropomorphical light biped robot. The robot presents a total of twelve degree of freedom that will permit it to act a walk in a three dimensional space, right now tested only in simulation. Each joint resemble the functionalities of the human articulation and is moved by tendon connected with actuator located in the robot’s pelvis. We implemented and tested an innovative actuator that permits to set the joint stiffness in real time maintaining a simple position control paradigm. The controller is able to estimate the external load measuring the spring deflection and demonstrated to be particularly robust respect to system uncertainties, such as inertia value changes. Comparing the resulting control law with existing models we found several similarities with the Equilibrium Point Theory.
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    An Adaptive Voltage Control Strategy of Three- Phase Inverter for Standalone Distributed Generation Systems
    (2012) Do, Ton Duc; Leu, Viet Quoc; Choi, Young-Sik; Choi, Han Ho; Jung, Jin-Woo
    This paper proposes an adaptive control method of three-phase inverter for standalone distributed generation systems (DGSs). The proposed voltage controller includes two control terms: an adaptive compensating term and a stabilizing term. The adaptive compensating control term is constructed to avoid directly calculating the time derivatives of state variables. Meanwhile, the stabilizing control term is designed to asymptotically stabilize the error dynamics of the system. Also, a fourth-order optimal load current observer is proposed to reduce the number of current sensors and enhance the system reliability and cost effectiveness. Stability of the proposed voltage controller and the proposed load current observer is fully proven by using Lyapunov theory. The proposed control system can establish good voltage regulation such as fast dynamic response, small steady state error, and low total harmonic distortion (THD) under sudden load change, unbalanced load, and nonlinear load. Finally, the validity of the proposed control strategy is verified through simulations and experiments on a prototype DGS testbed with a TMS320F28335 DSP. For a comparative study, the feedback linearization for multi-input and multi-output (FLMIMO) control scheme is implemented and its results are presented in this paper
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    An Electromagnetic Steering System for Magnetic Nanoparticle Drug Delivery
    (2015) Do, Ton Duc; Noh, Yeongil; Kim, Myeong Ok; Yoon, Jungwon
    Targeted delivery of pharmaceutical agents to the brain using magnetic nanoparticles (MNPs) is an efficient technique to transport molecules to disease locations. MNPs can cross the blood–brain barrier (BBB) and can be concentrated at a specific location in the brain using non-invasive electromagnetic forces. The proposed EMA consists of two coil-core system. The cores are added in the center of each coil to concentrate the flux in the region of interest. The EMA can enhance the gradient field 10 times compared to only coil system and generate the maximum magnetic field of 160 mT and 5.6 T/m. A 12-kW direct-current power supply was used to generate sufficient magnetic forces on the MNPs by regulating the input currents of the coils. Effective guidance of MNPs is demonstrated via simulations and experiments using 800-nm-diameter MNPs in a Y-shaped channel. The developed EMA system has high potentials to increase BBB crossing of MNPs for efficient drug targeting to brain regions
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    An Optimized Field Function Scheme for Nanoparticle Guidance in Magnetic Drug Targeting systems
    (IEEE, 2015) Do, Ton Duc; Noh, Yeongil; Kim, Myeong Ok; Yoon, Jungwon
    Magnetic drug targeting is an approach to guide and concentrate magnetic nanoparticles (MNPs) into the diseased target organ after being injected into blood vessels. Although many works for drug targeting have been conducted, there are few studies on delivering the nanoparticles to the target region. Drug delivery performance has not been addressed sufficiently or fully. In this paper, we investigate the effect of dominant factors to MNPs delivery performance. Then, an optimized field function scheme with a pulsed magnetic actuation is proposed to significantly improve the MNPs guidance performance. With a specific condition of blood vessel size, particle size, and applied magnetic field, the optimized parameters of the field function are selected through extensive simulation studies. We find out that the optimal negative and positive time for the magnetic pulsed field mainly depends on the exit time for particles to reach the bifurcation and the critical time as the maximum time for them to reach the vessels wall, respectively. With the chosen parameters, we show that ratios of correctly guided particles in a Y-channel are reached to 100%. In addition, to minimize the power consumption, a modified field function (MFF) scheme is introduced. The MFF includes a no-power time, called zero-time, between the positive and negative time. It is shown that with the proposed MFF, the energy consumption and the heating problem of the actuator system can be significantly reduced. Therefore, the proposed guidance scheme for MNPs can overcome the sticking issue and maximize the guidance performance as well as reducing the power consumption. It should be noted that the MFF can be easily implement by programmable DC power supplies connected to electromagnetic coils
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    Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle
    (2015) Asl, Hamed Jabbari; Do, Ton Duc
    This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of ow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic ow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are de ned from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the transla- tional dynamics of the system associated with the target motion, image depth and external disturbances. Simulation results and a comparison study are presented which demonstrate the e ectiveness of the proposed approach.
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    Augmenting variable stiffness actuation using reaction wheels
    (IEEE Access, 2016) Baimyshev, Almaskhan; Zhakatayev, Altay; Varol, Huseyin Atakan
    A branch of robotics, variable impedance actuation, along with one of its subfields variable stiffness actuation (VSA), is gaining momentum recently. There have been many thorough studies earlier in the design and recently in the control of these systems. The performance of these systems is mainly limited by their physical constraints, such as actuator nominal torque and maximum elastic element stiffness. This paper discusses the integration of reaction wheels to VSA systems and using reactive torques to improve the performance of the combined system. Since the compliant nature of VSA mechanisms is often associated with cyclic motion, reactive torques can be used to amplify the robot motion and accumulate more energy in the elastic elements in a given period of time. After presenting our modeling and control framework for reaction wheel-integrated VSA robots, we benchmark the performance of a reaction wheel-integrated VSA system using an explosive ball throwing task. Specifically, extensive simulation and real-world experiments are conducted with three different configurations: VSA-only, reaction wheel-only, and reaction wheel-integrated VSA. The results of these experiments show the benefits of reaction wheel-integrated VSA robots compared with the two other configurations.
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    Brain-Computer Interface Humanoid Pre-trained for Interaction with People
    (Nazarbayev University School of Science and Technology, 2018-03-08) Saduanov, Batyrkhan; Tokmurzina, Dana; Alizadeh, Tohid; Abibullaev, Berdakh
    People with the disabilities are in need to have an assistive technology that will alleviate their life through improving its social aspects. This article presents a Brain-Computer Interface (BCI) based remote presence system for humanoid NAO robot. The system would be useful for partially or fully paralyzed patients to interact with people and live active social life. A P300 based BCI is used to control high-level desires of the humanoid and visual stimulus presentation is implemented to control a humanoid robot. ”Programming by Demonstration (PbD)” methods are used to train the robot to perform human interactive actions and NAO robot native speller is used to talk with people. In general, the proposed solution combines two major techniques: Programming by demonstration and BCI. An experiment is designed and conducted on 5 different healthy subjects to perform a handshake, waving, walking and etc., verifying the applicability of the proposed approach.
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    Children’s perception of synthesized voice: Robot’s gender, age and accent
    (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015) Sandygulova, Anara; O’Hare, Gregory M. P.
    This paper presents a study of children’s responses to the perceived gender and age of a humanoid robot Nao that communicated with four genuine synthesized child voices. This research investigates children’s preferences for an English accent. Results indicate that manipulations of robot’s age and gender are successful for all voice conditions, however some voices are preferred over the others by children in Ireland.
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    Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control
    (IEEE Access, 2015-04-10) Zhakatayev, Altay; Rubagotti, Matteo; Varol, Huseyin Atakan
    Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently the focus is shifting to the control of these systems. Control of VSA robots is challenging due to the intrinsic nonlinearity of their dynamics and the need to satisfy constraints on input and state variables.Contrary to the partially open-loop state-of-the-art approaches, in this paper, we present a close-loop control framework for VSA robots leveraging recent increases in computational resources and advances in optimization algorithms. In particular, we generate reference trajectories by means of open-loop optimal control, and track these trajectories via nonlinear model predictive control in a closed-loop manner. In order to show the advantages of our proposed scheme with respect to the previous (partially open-loop) ones, extensive simulation and real-world experiments were conducted using a two link planar manipulator for a ball throwing task. The results of these experiments indicate that the closed-loop scheme outperforms the partially open loop one due to its ability to compensate for model uncertainties and external disturbances, while satisfying the imposed constraints.
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    Cluster-head based feedback for simplified time reversal prefiltering in ultra-wideband systems
    (Physical Communication, 2017-12-01) Soleimani, Hossein; Tomasin, Stefano; Alizadeh, Tohid; Shojafar, Mohammad; Hossein, Soleimani
    Abstract Time-reversal prefiltering (TRP) technique for impulse radio (IR) ultra wide-band (UWB) systems requires a large amount of feedback to transmit the channel impulse response from the receiver to the transmitter. In this paper, we propose a new feedback design based on vector quantization. We use a machine learning algorithm to cluster the estimated channels into several groups and to select the channel cluster heads (CCHs) for feedback. In particular, CCHs and their labels are recorded at both side of the UWB transceivers and the label of the most similar CCH to the estimated channel is fed back to the transmitter. Finally, the TRP is applied using the feedback CCH. The proposed digital feedback provides three main advantages: (1) it significantly reduces the dedicated bandwidth required for feedback; (2) it considerably improves the speed of transceivers; and, (3) it is robust to noise in the feedback channel since few bytes are required to send the codes that can be heavily error protected. Numerical results on standard UWB channel models are discussed, showing the advantage of the proposed solution.
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    Data Aggregation in Wireless Sensor Networks with Multiple Sinks
    (Nazarbayev University School of Science and Technology, 2017-04) Yestemirova, Gaukhar
    The invention of wireless sensor networks (WSNs) has caused a technological breakthrough in almost all industry fields that need to acquire regular and reliable real-time data from the field of interest. Today WSNs are used in many applications, including environmental, industrial, health care, and military. A WSN is a network comprised of sensors devices, usually called nodes, and a designated device called a sink to which nodes transmit their sensed data. Nodes are low-cost, battery-powered devices with limited memory and computational power. Usually WSNs are deployed and left unattended for a long time. During this time the WSN can experience different faulty scenarios. For example, nodes and sink can crash or communication between them can go down. In such cases, the network becomes useless as the sink will not be able to collect data from nodes. One way to increase the reliability of such WSNs is to deploy them with more than one sink so that when one sink goes down other sinks could forward collected data. A number of data collection protocols have been proposed so far. However, they have been proposed mainly for WSNs with a single sink. Existing protocols developed for WSNs with a single sink does not show the similar system efficiency to WSNs with multiple sinks. In this thesis work, we propose three data aggregation protocols for WSNs with multiple sinks: i) an adjusted form of Minimum Spanning Tree (MST); ii) two adjusted forms of Shortest Path Tree (SPT) and i) Maximum Spanning Backbone (MSB) that try to minimize the number of message transmissions during data collection. In all cases we first build a tree and then highlight the set of nodes that connect all the sinks and call them backbone nodes. These backbone nodes first collect the data from the nodes, then send aggregated data to all the sinks. We show the performance of our proposed protocols using simulation program. The simulation results from least to most backbone nodes as the following: MSB, two adjustments of SPT and MST.
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    Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy
    (Measurement, 2017-02-01) Abibullaev, Berdakh; An, Jinung; Lee, Seung Hyun; Moon, Jeon Il; Berdakh, Abibullaev
    Abstract The integration of Brain-Computer-Interfaces (BCI) into rehabilitation research is a promising approach that may substantially impact the rehabilitation success. Yet, there is still significant challenges that needs to be addressed before the BCI technology can be fully used effectively in a clinical setting as a neural prosthesis for motor impaired users. As it is still unknown whether the conventional BCI induction strategies that use different the types of stimuli and/or mental tasks induce cortical reorganization for disabled users. This paper presents a design and evaluation of a real-time Near-Infrared Spectroscopy (NIRS) based BCI protocol to control an external haptic device, and an interesting source of brain signals that may convey complementary information for inducing neuroplasticity. The protocol is based on the ideas derived from Mirror-based Therapy (MT) in which subjects not only perform literal motor imagery tasks but also combine their intents with visual action observation of a related motor imagery task. The NIRS-BCI system then commands a haptic device in real-time to move in opposing directions of leftward and rightward movement. We also compare the proposed protocol to the conventional limb motor imagery task and verify its efficacy with online decoding accuracies up to 94.99%. The initial validation of the experimental setup was done with seven healthy subjects. Nonetheless we contend that the design of the current NIRS-BCI method hold promise with patient populations for effective stroke rehabilitation therapy, because the beneficial effects of MT alone in post-stroke recovery has already been manifested in the literature.
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    Development of a Lightweight Biped Robot
    (Nazarbayev University School of Science and Technology, 2017-05) Aubakir, Bauyrzhan
    Robotics, as a research and technical field, finds inspiration in nature. In particular, bipedal robots, which structure and kinematics reproduce the lower limbs of a human body, are the first step toward functional humanoid robots. This document describes the development phases of a lightweight biped robot under construction at the department of Robotics and Mechatronics in Nazarbayev University. The mechanical design is the primary focus of this work; nevertheless, a big effort was also dedicated to formalize and realize the electrical, sensorial and software subsystems. By using 3D printing techniques and lightweight materials a lower power consumption and higher power over weight ratio was reached in comparison with state-of-the-art robots having comparable dimensions. Furthermore, thanks to a lower links inertia the system is inherently safer when operating in environment where humans are present. A detailed description of the robot kinematics and the methodology followed to dimension the actuation system is provided together with preliminary results on the execution of different postures and gaits.