IAES International Journal of Robotics and Automation (IJRA)
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Design and Fabrication of Delta Robot with Voice control
Get PDFThe objective of the project is to design and control the Delta robot with voice for pick and place operation using ARM7 processor. Till now there is no implementation of voice recognition and control in Delta robot. The maximum payload of the robot is 200grams-300grams. The robot has been made based on the SEQUENTIAL QUADRATIC PROGRAMMING. Various links of the robot are controlled using the servo motor and the gripper is separately controlled by a servo motor
A Techniques to Downgrade Objective Function in Parallel Robot Kinematics Problem
Get PDFQuadratic functions and quaternary functions are preferable forms solving parallel robot kinematics problems. In order to simplify and to use only one method to solve all forms of the objective functions, this article introduces prevalent techniques to downgrade mathematical model of the objective functions from quaternary function to quadratic function in parallel robot kinematics problem. By using equivalent alternative kinematic structure and additional mathematical constraints, we will change from the study of parallel robot kinematics problem with the form of quaternary objective function as the original configuration to equivalent alternative configuration in the form of quadratic objective function. The parallel robot kinematics problem based on alternative configuration with quadratic objective function is not only simpler but also helps to quickly identify the mathmatical relationships in the joint space and work space of parallel robot. Then, more accurate control solution of parallel robot kinematics problem can be identified. Moreover, by using techniques in this study, all forms of objective functions of parallel robot of any structure can be easily solved. The result from numerical simulation has been used to prove the presented approaches
Mobile Robot Localization: A Review of Probabilistic Map-Based Techniques
Get PDFThis work presents a comprehensive review of current probabilistic developments used to calculate position by mobile robots in indoor environments. In this calculation, best known as localization, it is necessary to develop most of the tasks delegated to the mobile robot. It is then crucial that the methods used for position calculations be as precise as possible, and accurately represent the location of the robot within a given environment. The research community has devoted a considerable amount of time to provide solutions for the localization problem. Several methodologies have been proposed the most common of which are based in the Bayes rule. Other methodologies include the Kalman filter and the Monte Carlo localization filter wich will be addressed in next sections. The major contribution of this review rests in offering a wide array of techniques that researchers can choose. Therefore, method-sensor combinations and their main advantages are displayed
Wall-E Surveyor Robot using Wireless Networks
Get PDFThe methods for autonomous navigation of a robot in a real world environment is an area of interest for current researchers. Although there have been a variety of models developed, there are problems with regards to the integration of sensors for navigation in an outdoor environment like moving obstacles, sensor and component accuracy. This paper details an attempt to develop an autonomous robot prototype using only ultrasonic sensors for sensing the environment and GPS/ GSM and a digital compass for position and localization. An algorithm for the navigation based on reactive behaviour is presented. Once the robot has navigated to its final location based on remote access by the owner, it surveys the geographical region and uploads the real time images to the owner using an API that is developed for the Raspberry PI’s kernel
The Mobile Robot HILARE: Dynamic Modeling and Motion Simulation
Get PDFTo perform mission in variant environment, several types of mobile robot has been developed an implemented. The mobile robot HILARE is a known wheeled mobile robot which has two fixed wheels and an off-entered orientable wheel. Due to extended application of this robot, its dynamic analysis has attracted a great deal of interests. This article investigates dynamic modeling and motion analysis of the mobile robot HILARE. As the wheels of the robot have kinematic constraints, the constraints of wheels are taken into consideration and the matrix form of the kinematic model of the robot is derived. Furthermore, dynamic model of the robot is developed by consideration of kinematic constraints. To derive dynamic equations of the robot, the Lagrange multiplier method is employed and the governing equations of the robot in state-pace form are presented. Then, some simulations are presented to show applicability of the proposed formulation for dynamic analysis of the mobile robot HILARE
Obstacle Avoidace Robot Using LabView
Get PDFThe concept of path planning and collision avoidance are two of the most common theories applied for designing and developing in advanced autonomous robotics applications. NI LabView makes it possible to implement real-time processor for obstacle avoidance. The obstacle avoidance strategy ensures that the robot whenever senses the obstacle stops without being collided and moves freely when path is free, but sometimes there exists a probability that once the path is found free and the robot starts moving, then within a fraction of milliseconds, the robot again sense the obstacle and it stops. This continuous swing of stop and run within a very small period of time may cause heavy burden on the system leading to malfunctioning of the components of the system. This paper deals with overcoming this drawback in a way that even after the robot calculates the path is free then also it will wait for a specific amount of time before running it. So as to confirm that if again the sensor detects the obstacle within that specified period then robot don’t need to transit its state suddenly thus avoiding continuous transition of run and stop. Thus it reduces the heavy burden on the system
Integration and Simulations of INS/GNSS System using the Approach of Carrier Phase Measurements
Get PDFThis paper discusses the techniques of attitude, velocity ad position estimation from GNSS carrier phase measurements, and investigates the performance of the lower precision MEMS-based INS/GNSS system based on carrier phase measurements. Double differenced carrier phase measurements provide more accurate velocity and position estimation compared to code and Doppler measurements. However, integer ambiguity is required to be removed for precise positioning. Multiples antennae approach is used to derive the attitude information from carrier phase measurements in order to control the large initial misalignment angles for initialization of the integration process or to utilize during benign dynamics. Lever arm effect is considered to compensate for the separation of GNSS antenna and IMU location. The derived three GNSS observables are used to correct the INS through optimal Kalman filtering in a closed loop. Simulation results indicates the effectiveness of the integrated system for airborne as well as for land navigation vehicles. This paper discusses the techniques of attitude, velocity ad position estimation from GNSS carrier phase measurements, and investigates the performance of the lower precision MEMS based INS/GNSS system based on carrier phase measurements. Double differenced carrier phase measurements provide more accurate velocity and position estimation compared to code and Doppler measurements. However, integer ambiguity is required to be removed for precise positioning. Multiples antennae approach is used to derive the attitude information from carrier phase measurements in order to control the large initial misalignment angles for initialization of the integration process or to utilize during benign dynamics. Lever arm effect is considered to compensate for the separation of GNSS antenna and IMU location. The derived three GNSS observables are used to correct the INS through optimal Kalman filtering in a closed loop. Simulation results indicates the effectiveness of the integrated system for airborne as well as for land navigation vehicles
Autonomous Lavatory Cleaning System
Get PDFThe application of integrated robotics is becoming increasingly commonplace in day to day applications. The idea presented in this paper seeks to provide a convenient and a hassle-free means of cleaning public toilets whilst maintaining hygienic and sanitary standards. By using a counter to record the number of times of usage, a line follower mechanism to guide the robot and an RFID module to initiate the flushing, the cleaning operation is fully automated and requires low operational power. Furthermore, a robotic arm is part of the module, so as to thoroughly clean the toilet bowl. Such a provision will curtail the role of manpower in maintenance of public toilets to a great degree, and thus, serves as a win-win situation; a revolting objective is accomplished with considerable ease
Using Deep Learning for Human Computer Interface via Electroencephalography
Get PDFIn this paper, several techniques used to perform EEG signal pre-processing, feature extraction and signal classification have been discussed, implemented, validated and verified; efficient supervised and unsupervised machine learning models, for the EEG motor imagery classification are identified. Brain Computer Interfaces are becoming the next generation controllers not only in the medical devices for disabled individuals but also in the gaming and entertainment industries. In order to build an effective Brain Computer Interface, it is important to have robust signal processing and machine learning modules which operate on the EEG signals and estimate the current thought or intent of the user. Motor Imagery (imaginary hand and leg movements) signals are acquired using the Emotiv EEG headset. The signal have been extracted and supplied to the machine learning (ML) stage, wherein, several ML techniques are applied and validated. The performances of various ML techniques are compared and some important observations are reported. Further, Deep Learning techniques like autoencoding have been used to perform unsupervised feature learning. The reliability of the features is presented and analyzed by performing classification by using the ML techniques. It is shown that hand engineered ‘ad-hoc’ feature extraction techniques are less reliable than the automated (‘Deep Learning’) feature learning techniques. All the findings in this research, can be used by the BCI research community for building motor imagery based BCI applications such as Gaming, Robot control and autonomous vehicles
A Brief Survey Paper on Multi-Legged Robots
Get PDFThis paper presents a brief survey on multi-legged robots and their applications in agriculture such as for harvesting. Multi-legged robots have the benefit of more flexibility and adapt to different rough terrain in a better way. They also have very important applications in fulfilling the dangerous tasks such as mine detecting