Embedded System for Motion Control of an Omnidirectional Mobile Robot

In this paper, an embedded system for motion control of omnidirectional mobile robots is presented. An omnidirectional mobile robot is a type of holonomic robots. It can move simultaneously and independently in translation and rotation. The RoboCup small-size league, a robotic soccer competition, is chosen as the research platform in this paper. The first part of this research is to design and implement an embedded system that can communicate with a remote server using a wireless link, and execute received commands. Second, a fuzzy-tuned proportional–integral (PI) path planner and a related low-level controller are proposed to attain optimal input for driving a linear discrete dynamic model of the omnidirectional mobile robot. To fit the planning requirements and avoid slippage, velocity, and acceleration filters are also employed. In particular, low-level optimal controllers, such as a linear quadratic regulator (LQR) for multiple-input-multiple-output acceleration and deceleration of velocity are investigated, where an LQR controller is running on the robot with feedback from motor encoders or sensors. Simultaneously, a fuzzy adaptive PI is used as a high-level controller for position monitoring, where an appropriate vision system is used as a source of position feedback. A key contribution presented in this research is an improvement in the combined fuzzy-PI LQR controller over a traditional PI controller. Moreover, the efficiency of the proposed approach and PI controller are also discussed. Simulation and experimental evaluations are conducted with and without external disturbance. An optimal result to decrease the variances between the target trajectory and the actual output is delivered by the onboard regulator controller in this paper. The modeling and experimental results confirm the claim that utilizing the new approach in trajectory-planning controllers results in more precise motion of four-wheeled omnidirectional mobile robots.

[1]  A.P. Moreira,et al.  Practical Approach of Modeling and Parameters Estimation for Omnidirectional Mobile Robots , 2009, IEEE/ASME Transactions on Mechatronics.

[2]  Yan Jiang,et al.  An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot , 2012, Journal of Zhejiang University SCIENCE C.

[3]  Woei Wan Tan,et al.  Stable adaptive fuzzy PD plus PI controller for nonlinear uncertain systems , 2011, Fuzzy Sets Syst..

[4]  S. Abraham Lincoln,et al.  A MODEL REFERENCE-BASED FUZZY ADAPTIVE PI CONTROLLER FOR NON-LINEAR LEVEL PROCESS SYSTEM , 2013 .

[5]  Raffaello D'Andrea,et al.  Near-optimal dynamic trajectory generation and control of an omnidirectional vehicle , 2004, Robotics Auton. Syst..

[6]  Eric Monacelli,et al.  A fuzzy-based reactive controller for a non-holonomic mobile robot , 2004, Robotics Auton. Syst..

[7]  Raffaello D'Andrea,et al.  Trajectory generation and control for four wheeled omnidirectional vehicles , 2006, Robotics Auton. Syst..

[8]  Manuela Veloso,et al.  CMDragons 2010 Team Description , 2010 .

[9]  Zhang Jia-sheng Maximum Power Point Tracking Control of the Wind Energy Generation System With Direct-driven Permanent Magnet Synchronous Generators , 2009 .

[10]  Maani Ghaffari Jadidi,et al.  Model-based PI-fuzzy control of four-wheeled omni-directional mobile robots , 2011, Robotics Auton. Syst..

[11]  Tufan Kumbasar,et al.  An Open Source Matlab/Simulink Toolbox for Interval Type-2 Fuzzy Logic Systems , 2015, 2015 IEEE Symposium Series on Computational Intelligence.

[12]  Kanjanapan Sukvichai,et al.  Robot Hardware, Software, and Technologies behind the SKUBA Robot Team , 2012, RoboCup.

[13]  David Sotelo,et al.  EAGLE KNIGHTS: SMALL SIZE ROBOCUP SOCCER TEAM , 2005 .

[14]  Leonids Ribickis,et al.  Energy efficient use of robotics in the automobile industry , 2011, 2011 15th International Conference on Advanced Robotics (ICAR).

[15]  Jongeun Choi,et al.  Solutions to the Inverse LQR Problem With Application to Biological Systems Analysis , 2015, IEEE Transactions on Control Systems Technology.

[16]  Jang Myung Lee,et al.  Balancing and Velocity Control of a Unicycle Robot Based on the Dynamic Model , 2015, IEEE Transactions on Industrial Electronics.

[17]  Zhichao Chen,et al.  Qualitative Vision-Based Path Following , 2009, IEEE Transactions on Robotics.

[18]  Ahmad Fakharian,et al.  Fuzzy adaptive PI control of omni-directional mobile robot , 2013, 2013 13th Iranian Conference on Fuzzy Systems (IFSC).

[19]  Christof Röhrig,et al.  Localization of an omnidirectional transport robot using IEEE 802.15.4a ranging and laser range finder , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Yiguang Hong,et al.  Distributed Continuous-Time Algorithm for Constrained Convex Optimizations via Nonsmooth Analysis Approach , 2015, IEEE Transactions on Automatic Control.

[21]  Maani Ghaffari Jadidi,et al.  Trajectory planning optimization with dynamic modeling of four wheeled omni-directional mobile robots , 2009, 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA).

[22]  Ron Alterovitz,et al.  Stochastic Extended LQR for Optimization-Based Motion Planning Under Uncertainty , 2016, IEEE Trans Autom. Sci. Eng..

[23]  Kim-Fung Man,et al.  An optimal fuzzy PID controller , 2001, IEEE Trans. Ind. Electron..

[24]  D. Naidu,et al.  Optimal Control Systems , 2018 .

[25]  J. Jim Zhu,et al.  Omni-directional mobile robot controller based on trajectory linearization , 2008, Robotics Auton. Syst..

[26]  I. Iancu A Mamdani Type Fuzzy Logic Controller , 2012 .

[27]  Stefan Preitl,et al.  PI-Fuzzy controllers for integral plants to ensure robust stability , 2007, Inf. Sci..

[28]  Yodyium Tipsuwan,et al.  Implementation of Torque Controller for Brushless Motors on the Omni-directional Wheeled Mobile Robot , 2017, ArXiv.

[29]  Rong-Jong Wai,et al.  Reachable Set Estimation and Decentralized Controller Design for Large-Scale Nonlinear Systems With Time-Varying Delay and Input Constraint , 2017, IEEE Transactions on Fuzzy Systems.

[30]  B. Anderson,et al.  Optimal control: linear quadratic methods , 1990 .