Sensorless position and speed control of differential drive mobile robot

  • Hiba Hliwa Tishreen University
  • Bassam Atieh Tishreen University
Keywords: Sensorless control, motor drive, actuators

Abstract

Differential Drive Mobile Robot is one of the most common and widely used mobile robots. It tracks the desired path depending on its velocity and position information come from various kind of sensors, which detect the robot movement regardless the reasons of the motion (actuators).Differential Drive Mobile Robot is one of the most common and widely used mobile robots. It tracks the desired path depending on its velocity and position information come from various kind of sensors, which detect the robot movement regardless the reasons of the motion (actuators). This research uses Sensorless control based on studying the actuator’s behaviors, choosing the parameters that express its output, finding the relationship between these parameters and the mechanical variables of the robot, and using them in driving the robot to its goal. This research could increase the efficiency of the DC motor and drive robot to its target with acceptable accuracy. Which open doors at further work on monitoring the performance of electrical actuators and get more comprehensive information about the robot to benefit from them to improve the robot performance.

Author Biography

Bassam Atieh, Tishreen University

Assistant  Professor, Mechatronics Department , Mechanical And Electrical Engineering

References

Adewusi, S., 2016. Modeling and Parameter Identification of a DC Motor Using Constraint Optimization Technique. IOSR Journal of Mechanical and Civil Engineering (IOSR - JMCE) 13, 46–56.
Ahmad Abu Hatab, R.D., 2013. Dynamic Modelling of Differential-Drive Mobile Robots using Lagrange and Newton-Euler Methodologies: A Unified Framework. Advances in Robotics & Automation 02.
Alasooly, H., 2011. CONTROL OF DC MOTOR USING DIFFERENT CONTROL STRATEGIES. Global Journal of Technology & Optimization (GJTO) 2, 8.
Alatise, M., Hancke, G., 2017. Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter. Sensors 17, 2164.
Bature, A.A., Buyamin, S., Ahmad, M.N., Muhammad, A.A., 2015. Sensorless position and velocity estimation of two wheeled inverted pendulum mobile robot, in: ControlConference(ASCC),201510thAsian. IEEE, pp. 1–4.
Chen, L., Li, J., Ding, R., 2011. Identification for the second-order systems based on the step response. Mathematical and Computer Modelling 53, 1074–1083.
Chen, X., Gao, Z., 2017. Indoor ultrasonic positioning system of mobile robot based on TDOA ranging and improved trilateral algorithm, in: Image,Vision Computing (ICIVC), 2017 2nd International Conference. IEEE, pp. 923–927.
Cho, B.-S., Moon, W., Seo, W.-J., Baek, K.-R., 2011. A dead reckoning localization system for mobile robots using inertial sensors and wheel revolution encoding. Journal of Mechanical Science and Technology 25, 2907–2917.
Cristoforis, P.D., 2013. Sistema de navegaci´on monocular para robots m´oviles en ambientes interiores/exteriores.
Doisy, G., 2012. Sensorless collision detection and control by physical interaction for wheeled mobile robots, in: Proceedings seventh annual ACM/IEEE international conferenceHumanRobotInteraction. ACM, pp. 121–122.
Duchoň, F., Babinec, A., Kajan, M., Beňo, P., Florek, M., Fico, T., Jurišica, L., 2014. Path Planning with Modified a Star Algorithm for a Mobile Robot. Procedia Engineering 96, 59–69.
Li, Y., Ji, Q., Zhu, Y., 2017. An Indoor Mobile Robot Localization Method Based on Information Fusion. Computing 5, 52–58.
Mathew, R., Hiremath, S.S., 2016. Trajectory Tracking and Control of Differential Drive Robot for Predefined Regular Geometrical Path. Procedia Technology 25, 1273–1280.
Nasir, A.K., Roth, H., 2012. Pose Estimation By Multisensor Data Fusion Of Wheel Encoders, Gyroscope, Accelerometer And Electronic Compass. IFAC Proceedings Volumes 45, 49–54.
Nise, N.S., 2014. Control Systems Engineering, 7th Edition. Wiley, New York.
Seo, W., Baek, K.-R., 2017. Indoor Dead Reckoning Localization Using Ultrasonic Anemometer with IMU. Journal of Sensors 2017, 1–12.
Sobh, T.M., Dekhil, M., Efros, A.A., 1997. Robust Sensing for Mobile Robot Control. IFAC Proceedings Volumes 30, 459–464.
Vivacqua, R., Vassallo, R., Martins, F., 2017. A Low Cost Sensors Approach for Accurate Vehicle Localization and Autonomous Driving Application. Sensors 17, 2359.
Xu, H., Ding, Y., Li, P., Wang, R., Li, Y., 2017. An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor. Sensors 17, 1806.
Ye, J., 2013. Tracking control of two-wheel driven mobile robot using compound sine function neural networks. Connection Science 25, 139–150.
Published
2018-08-16
How to Cite
Hliwa, H., & Atieh, B. (2018). Sensorless position and speed control of differential drive mobile robot. Majlesi Journal of Mechatronic Systems, 7(2), 47-53. Retrieved from https://ms.majlesi.info/index.php/ms/article/view/356
Section
Articles