1. A Force-Controlled Portrait Drawing Robot
A Force-Controlled Portrait Drawing Robot
There has been a lot of research in recreational uses of robots. A robot drawing the portrait of a human face is one such famous task. This makes the robot behavior more human-like and entertaining. There have been several demonstrations of portrait drawing robots in past few years. But the existing techniques can draw only on pre-calibrated and flat surfaces. This paper demonstrates a robot equipped with force sensing capability that can draw portraits on a non-calibrated, arbitrarily shaped surface. The robot is able to draw on a non-calibrated surface by orienting its drawing pen normal to the drawing surface, the penjs-orientation being computed from the forces being sensed. In this way, the robot is also able to draw portraits on arbitrarily shaped surfaces without knowing the surface geometry. This avoids the need for calibration of robot with respect to the drawing surface. A number of portraits were drawn successfully on a flat surface without calibration. Also a map outline was drawn on a spherical globe to demonstrate the ability of robot to draw on an arbitrarily shaped surface.
2.Brain-computer interface and Arduino microcontroller family software interconnection solution
Brain-computer interface and Arduino microcontroller family software interconnection solution
Brain-Computer Interface (BCI) is the modern approach to the construction of the Human-Machine Interface (HMI) that interconnects human brain and the machine and allows to send commands to the machine directly from the central nervous system (CNS) and especially the brain. Great popularity of the Arduino microcontroller board family and integration of its members into many projects including amateur, professional, industrial and scientific solutions impelled us to design software solution, that helps integrate Brain Computer Interface comprising Emotiv EPOC Neuroheadset with Arduino microcontroller boards. The paper introduces concept of the Brain-Computer Interface in its first section and possibilities of its use. Next section of the paper describes Emotiv EPOC Neuroheadset, which is the part of the BCI, with function of the electroencephalograph (EEG) that non-invasively monitors the electromagnetic manifestations of neural activity of the human central nervous system (CNS), mainly the brain. Using the proprietary software installed on the host computer software transforms acquired signals into the commands that are then executed via third party software. Another part of the paper introduces Arduino microcontroller board family and the last part describes proposed software solution that provides software interface between Emotiv EPOC Neuroheadset software and Arduino microcontroller boards.
3.Central Pattern Generators with Biology Observation for the Locomotion Control of Hexapod Robots
Central Pattern Generators with Biology Observation for the
Locomotion Control of Hexapod Robots
This paper focuses on the control of hexapod locomotion based on a model of artificial central pattern generators (CPGs). CPG-based controllers are capable of producing coordinated patterns in open loops and rhythmic activities in certain joints. However, existing methods usually have too many parameters to set and lack unified expressions to achieve desired gaits for multiple legged robots. In this contribution, biology observation and CPG modeling are employed to build the controller. Coupled nonlinear oscillators serve as the elementary unit and coupling terms are discussed to get the typical hexapod locomotion patterns. At first, we collect the locomotion date of real cockroaches Blaptica Dubia and complete some data analysis with the approach of image processing. Then modified Hopf oscillators are applied to separately control the swing phase and stance phase, and analytical formulation of coupling terms is adopted to construct the control architecture. Next, we modulate the proposed controller on the basis of three-dimensional trace of cockroaches by kinematic analysis and curve fitting. Finally, we build and control two different hexapod robots (’hexabot’ and ’smarbot’) to confirm the validation of the approach.
4.Development of a Brain-Computer Interface Based on Visual Stimuli for the Movement of a Robot Joints
Development of a Brain-Computer Interface Based on Visual Stimuli for the Movement of a Robot Joints
This paper presents a brain computer interface (BCI) to control a robotic arm by brain signals from visual stimuli. The following signal processing steps were established; acquisition of brain signals by electroencephalography (EEG) electrodes; noise reduction; extraction of signal characteristics and signal classification. Reliable brain signals were obtained by the use of the Emotiv EPOC® commercial hardware. The OpenViBE® commercial software was used to program the signal processing algorithms. By using Matlab® together with an Arduino® electronic board, two servo motors were controlled to drive two joints of a 5 degrees-of-freedom robot commanded by P300-type evoked potential brain signals from visual stimulation when a subject concentrates on particular images from an image matrix displayed in the computer screen. The experiments were conducted with and without hearing and visual noise (artifacts) to find out the noise influence in the signal classification outcome. The obtained experimental results presented an efficiency in the identification stage up to 100% with and without hearing noise conditions. However, under visual noise conditions a maximum efficiency of 50% was reached. The experiments for the servomotors control were carried out without noise, reaching an efficiency of 100% in the identification stage.
5.Development of Stereo Vision and Master-Slave Controller for a Compact Surgical Robot System
Development of Stereo Vision and Master-Slave Controller for a Compact Surgical Robot System
In this paper, we have developed a robotic surgical system, which provides a low-cost, compact and modular structure for simulation and evaluation of tele-operation controller design. A 3D stereo vision tracking subsystem for the tele-surgery system has been proposed to render real-time surgery site image to the surgeon, while the tele-surgery subsystem enables the surgeon to perform tele-operations. The designed controller generated smooth trajectories on the compact surgical system, which could be further utilized as a standard tele-surgery training system.
6.Optimized Assistive Human–Robot Interaction Using Reinforcement Learning
Optimized Assistive Human–Robot Interaction Using Reinforcement Learning
Maintaining a reliable and cost effective operation in micro grids has significant importance. One factor required for optimal operation of the micro grid is to keep a certain energy reserve without unnecessary cost to satisfy load variations. In this paper, an optimal reserve assessment of photovoltaic and fuel cell based micro grids are investigated while considering reliability and economic aspects. A typical residential load is predicted to introduce an optimal power sharing approach, and accordingly, to achieve reliable and cost effective system operation. Load sharing between sources in micro grids affects the cost, and also affects the source’s ability in responding to load variations. A nonlinear frequency droop scheme is then used as a tool to achieve the optimization objectives such that the operating cost is minimized without jeopardizing the micro grid’s ability of responding to sudden load variations. Presented results confirm the validity of the power sharing approach and verify its effectiveness and feasibility.