Control system architecture for the investigation of motion control algorithms on an example of the mobile platform Rex

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Abstract

This paper presets the specification and implementation of the control system of the mobile platform Rex. The presented system structure and the description of its functioning result from the application of a formal method of designing such systems. This formalism is based on the concept of an embodied agent. The behaviours of its subsystems are specified in terms of transition functions that compute, out of the variables contained in the internal memory and the input buffers, the values that are inserted into the output buffers and the internal memory. The transition functions are the parameters of elementary actions, which in turn are used in behaviour patterns which are the building blocks of the subsystems of the designed control system. Rex is a skid steering platform, with four independently actuated wheels. It is represented by a single agent that implements the locomotion functionality. The agent consists of a control subsystem, a virtual effector and a virtual receptor. Each of those subsystems is discussed in details. Both the data structures and the transition functions defining their behaviours are described. The locomotion agent is a part of the control system of the autonomous exploration and rescue robot developed within the RobREx project.

[1] C. Zieliński, “Specification of behavioural embodied agents”, Fourth Int. Workshop on Robot Motion and Control (RoMoCo’04) 1, 79–84 (2004).

[2] S.H. Kaisler, Software Paradigms, Wiley Interscience, London, 2005.

[3] K. Sacha, Software Engineering, PWN, Warszawa, 2010, (in Polish).

[4] C. Zieliński, T. Kornuta, and M. Boryń, “Specification of robotic systems on an example of visual servoing”, 10th Int. IFAC Symp. on Robot Control (SYROCO 2012) 10, 45–50 (2012).

[5] T. Kornuta and C. Zieliński, “Robot control system design exemplified by multi-camera visual servoing”, J. Intelligent & Robotic Systems 1, 1–25 (2013).

[6] C. Zieliński and T. Kornuta, “Diagnostic requirements in multi-robot systems”, Intelligent Systems in Technical and Medical Diagnostics, pp. 345–356, Springer, Berlin, 2014.

[7] C. Zieliński, T. Kornuta, and T. Winiarski, “A systematic method of designing control systems for service and field robots”, 19-th IEEE Int. Conf. Methods and Models in Automation and Robotics, MMAR’2014 1, 1–14 (2014).

[8] C. Zieliński, “Transition-function based approach to structuring robot control software”, Robot Motion and Control, Lecture Notes in Control and Information Sciences 335, 265–286 (2006).

[9] C. Zieliński and T. Winiarski, “General specification of multi-robot control system structures”, Bull. Pol. Ac.: Tech. 58 (1), 15–28 (2010).

[10] C. Zieliński and T. Winiarski, “Motion generation in the MRROC++ robot programming framework”, Int. J. Robotics Research, 29 (4), 386–413 (2010).

[11] K. Tchoń and J. Jakubiak, “Endogenous configuration space approach to mobile manipulators: a derivation and performance assessment of Jacobian inverse kinematics algorithms”, Int. J. Contr. 76 (14), 1387–1419 (2003).

[12] D. Paszuk, K. Tchoń, and Z. Pietrowska, “Motion planning of the trident snake robot equipped with passive or active wheels”, Bull. Pol. Ac.: Tech. 60 (3), 547–555 (2012).

[13] M. Janiak and K. Tchon, “Constrained motion planning of non-holonomic systems”, Syst. Contr. Lett. 60 (8), 625–631 (2011).

[14] A. Ratajczak and K. Tchoń, “Multiple-task motion planning of non-holonomic systems with dynamics”, Mechanical Sciences 4 (1), 153–166 (2013).

[15] K. Tchoń, M. Janiak, K. Arent, and Ł. Juszkiewicz, ‘Motion planning for the mobile platform Rex”, in R. Szewczyk, C. Zieliński, and M. Kaliczyńska, eds., Recent Advances in Automation, Robotics and Measuring Techniques, pp. 497–506, Springer, Berlin, 2014.

[16] M. Janiak and K. Tchoń, “Constrained robot motion planning: Imbalanced jacobian algorithm vs. optimal control approach”, Methods and Models in Automation and Robotics (MMAR), 15th Int. Conf. 1, 25–30 (2010).

[17] B. Houska, H.J. Ferreau, and M. Diehl, “ACADO toolkit – an open-source framework for automatic control and dynamic optimization”, Optim. Control Appl. Meth. 32, 298–312 (2011).

[18] M. Diehl, H.J. Ferreau, and N. Haverbeke, “Efficient numerical methods for nonlinear MPC and moving horizon estimation”, Nonlinear Model Predictive Control, Lecture Notes in Control and Information Sciences 384, 391–417 (2009).

[19] G.V. Raffo, G.K. Gomes, J.E. Normey-Rico, C.R. Kelber, and L.B. Becker, “A predictive controller for autonomous vehicle path tracking”, Intelligent Transportation Systems, IEEE Trans. 10 (1), 92–102 (2009).

[20] M. Cholewiński, K. Arent, and A. Mazur, “Towards practical implementation of an artificial force method for control of the mobile platform Rex”, Recent Advances in Automation, Robotics and Measuring Techniques, of Advances in Intelligent Systems and Computing 267, 353–363 (2014).

[21] A. Mazur and M. Cholewiński, “Robust control of differentially driven mobile platforms”, Robot Motion and Control, in Control and Information Sciences 2011, 53–64 (2012).

[22] M. Diehl, H.G. Bock, H. Diedam, and P.-B. Wieber, “Fast direct multiple shooting algorithms for optimal robot control”, Fast Motions in Biomechanics and Robotics, Lecture Notes in Control and Information Sciences 340, 65–93 (2006).

[23] C. Zieliński, A. Rydzewski, and W. Szynkiewicz, “Multi-robot system controllers”, Proc. 5th Int. Symp. Methods and Models in Automation and Robotics 3, 795–800 (1998).

[24] J.V. Frasch, T. Kraus, W. Saeys, and M. Diehl, “Moving horizon observation for autonomous operation of agricultural vehicles”, Control Conf. (ECC), Eur. 3, 4148–4153 (2013).

[25] M. Zanon, J.V. Frasch, and M. Diehl, “Nonlinear moving horizon estimation for combined state and friction coefficient estimation in autonomous driving”, Control Conf. (ECC), Eur. 3, 4130–4135 (2013).

[26] H.J. Ferreau, T. Kraus, M. Vukov, W. Saeys, and M. Diehl, “High-speed moving horizon estimation based on automatic code generation”, Decision and Control (CDC), IEEE 51st Ann. Conf. 2, 687–692 (2012).

[27] A. Geiger, J. Ziegler, and C. Stiller, “StereoScan: Dense 3d reconstruction in real-time”, Intelligent Vehicles Symp. (IV), IEEE 1, 963–968 (2011).

[28] S.A. Mahmoudi, M. Kierzynka, P. Manneback, and K. Kurowski, “Real-time motion tracking using optical flow on multiple GPUs”, Bull. Pol. Ac.: Tech. 62 (1), 139–150 (2014).

[29] Xenomai, Real-Time Framework for Linux, http://www.xenomai.org.

[30] ROS, Robot Operating System, http://www.ros.org.

[31] OROCOS, Open Robot Control Software, http://www.orocos.org.

[32] Real Time Engineers Ltd., FreeRTOS, http://www.freertos.org.

[33] RTnet, Hard Real-Time Networking for Real-Time Linux, http://www.rtnet.org.

Bulletin of the Polish Academy of Sciences Technical Sciences

The Journal of Polish Academy of Sciences

Journal Information


IMPACT FACTOR 2016: 1.156
5-year IMPACT FACTOR: 1.238

CiteScore 2016: 1.50

SCImago Journal Rank (SJR) 2016: 0.457
Source Normalized Impact per Paper (SNIP) 2016: 1.239

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