Open Access Open Access  Restricted Access Subscription or Fee Access

VLSI Implementation of an Adaptable Localization System for All Unicycle Robot Platforms


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/iremos.v10i1.11288

Abstract


In this paper, a new adaptable odometric localization system (AOLS) with all unicycle robotic platforms is designed. For this, a variable kinematic model is synthesized with VHDL code, using the QUARTUS II software, and then implemented using an FPGA CYCLONE II. The proposed method is based on a recursive algorithm to calculate in real time the exact position, the final orientation of the robot, as well as position and orientation errors for a given destination. The system designed can be used in the case where the configuration of a robot changes during navigation, in order to reach unattainable destinations by the normal platform. Experimental results show that the implemented system is well suited with two unicycles robots of different sizes, and generates in real time a very fast and accurate calculation for different case studies.
Copyright © 2017 Praise Worthy Prize - All rights reserved.

Keywords


Adaptable Localization; Mobile Robotic; Unicycle Platform; VLSI Implementation

Full Text:

PDF


References


J. J. Leonard, H. F. Durrant-Whyte, Mobile robot localization by tracking geometric beacons, IEEE Transactions on robotics and Automation, Vol.7(3): 376-382, 1991.

Z. Zhang et al., A novel absolute localization estimation of a target with monocular visionOptik-International Journal for Light and Electron Optics, 124(12):1218-1223, 2013.
http://dx.doi.org/10.1016/j.ijleo.2012.03.032

J. Borenstein, L. Feng, Measurement and correction of systematic odometry errors in mobile robots, IEEE Transactions on robotics and automation, 12(6): 869-880, 1996.
http://dx.doi.org/10.1109/70.544770

B. Barshan, H. F Durrant-Whyte, Inertial navigation systems for mobile robots, IEEE Transactions on Robotics and Automation, 11(3): 328-342, 1995.
http://dx.doi.org/10.1109/70.388775

A. Martinelli et al., Simultaneous localization and odometry self calibration for mobile robot, Autonomous Robots, 22(1):pp. 75-85, 2007.
http://dx.doi.org/10.1007/s10514-006-9006-7

Ganganath, N., Leung, H.. Mobile robot localization using odometry and kinect sensor. In Emerging Signal Processing Applications (ESPA), 2012 IEEE International Conference on, pp. 91-94, January 2012.
http://dx.doi.org/10.1109/espa.2012.6152453

G. Oriolo et al., Humanoid odometric localization integrating kinematic, inertial and visual information, Autonomous Robots, 40(5): 867-879, 2016.
http://dx.doi.org/10.1007/s10514-015-9498-0

T. Nagata, G. Ishigami, Gyro-based odometry associated with steering characteristics for wheeled mobile robot in rough terrain. Advanced Robotics, 1-14. 2016
http://dx.doi.org/10.1080/01691864.2016.1241719

S. T. Pan, X. Y. Li, An FPGA-based embedded robust speech recognition system designed by combining empirical mode decomposition and a genetic algorithm, IEEE Transactions on Instrumentation and Measurement, 61(9):2560-2572, 2012.
http://dx.doi.org/10.1109/tim.2012.2190344

D. Zhang, H. Li, A stochastic-based FPGA controller for an induction motor drive with integrated neural network algorithms, IEEE Transactions on Industrial Electronics, 55(2):551-561. 2008.
http://dx.doi.org/10.1109/tie.2007.911946

H. Hagiwara, Y. Touma, K.. Asami, M. Komori, FPGA-Based Stereo Vision System Using Gradient Feature Correspondence, Journal of robotics and mechatronics, 27(6):681-690, 2015.
http://dx.doi.org/10.20965/jrm.2015.p0681

N. G. Johnson-Williams et al., Design of a real time FPGA-based three dimensional positioning algorithm, IEEE Transactions on Nuclear Science, 58(1):26-33, 2011.
http://dx.doi.org/10.1109/tns.2010.2093909

J. Rodriguez-Araujo et al., Field-programmable system-on-chip for localization of UGVs in an indoor ispace, IEEE Transactions on Industrial Informatics, 10(2):1033-1043, 2014.
http://dx.doi.org/10.1109/tii.2013.2294112

M. Dagbagi et al ADC-Based Embedded Real-Time Simulator of a Power Converter Implemented in a Low-Cost FPGA: Application to a Fault-Tolerant Control of a Grid-Connected Voltage-Source Rectifier, IEEE Transactions on Industrial Electronics, 63(2):1179-1190, 2016.
http://dx.doi.org/10.1109/tie.2015.2491883

Lentaris, G., Stamoulias, I., Soudris, D., & Lourakis, M.. HW/SW co-design and FPGA acceleration of visual odometry algorithms for rover navigation on Mars, IEEE Transactions on Circuits and Systems for Video Technology 76(8):1563, 2015.
http://dx.doi.org/10.1109/tcsvt.2015.2452781

L.E. Dubins, On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents, American Journal of Mathematics 79 (3):497–516.1957.
http://dx.doi.org/10.2307/2372560

A. Z. Jidin, T. Sutikno, FPGA Implementation of Low-Area Square Root Calculator, TELKOMNIKA (Telecommunication Computing Electronics and Control), 13(4):1145-1152, 2015.
http://dx.doi.org/10.12928/telkomnika.v13i4.1894

Deepak, F., Vairamani, R., Ranjitha, R., FPGA Implementation of Z-Source Multilevel Inverter Fed Induction Motor Drives, (2014) International Review of Electrical Engineering (IREE), 9 (4), pp. 735-742.
http://dx.doi.org/10.15866/iree.v9i4.2248

Krim, S., Gdaim, S., Mtibaa, A., Faouzi Mimouni, M., Real Time Implementation of High Performance’s Direct Torque Control of Induction Motor on FPGA, (2014) International Review of Electrical Engineering (IREE), 9 (5), pp. 919-929.
http://dx.doi.org/10.15866/iree.v9i5.3664

Subrahmanyeswara Rao, T., Aswini, T., Venu Gopal Rao, M., Implementation of Low-Power Adaptive Viterbi Decoder for Wireless Communication, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5 (6), pp. 316-322.
http://dx.doi.org/10.15866/irecap.v5i6.7421


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize