A linear programming methodology for approximate dynamic programming

[EN] The linear programming (LP) approach to solve the Bellman equation in dynamic programming is a well-known option for finite state and input spaces to obtain an exact solution. However, with function approximation or continuous state spaces, refinements are necessary. This paper presents a methodology to make approximate dynamic programming via LP work in practical control applications with continuous state and input spaces. There are some guidelines on data and regressor choices needed to obtain meaningful and well-conditioned value function estimates. The work discusses the introduction of terminal ingredients and computation of lower and upper bounds of the value function. An experimental inverted-pendulum application will be used to illustrate the proposal and carry out a suitable comparative analysis with alternative options in the literature.The authors are grateful for the financial support of the Spanish Ministry of Economy and the European Union, grant DPI2016-81002-R (AEI/FEDER, UE), and the PhD grant from the Government of Ecuador (SENESCYT).Diaz, H.; Sala, A.; Armesto Ángel, L. (2020). A linear programming methodology for approximate dynamic programming. International Journal of Applied Mathematics and Computer Science (Online). 30(2):363-375. https://doi.org/10.34768/amcs-2020-0028S36337530

Low-cost Printable Robots in Education

The final publication is available at Springer via http://dx.doi.org/10.1007/s10846-015-0199-xThe wider availability of 3D printing has enabled small printable robots (or printbots) to be incorporated directly into engineering courses. Printbots can be used in many ways to enhance lifelong learning skills, strengthen understanding and foster teamwork and collaboration. The experiences outlined in this paper were used in our teaching during the last academic year, although much of the methodology and many of the activities have been used and developed over the past 8 years. They include project based assignments carried out by multidisciplinary and multicultural teams, a number of theoretical and practical classroom and laboratory activities all aimed at familiarizing students with fundamental concepts, programming and simulation, and which now form part of our regular robotics courses, and some brief descriptions of how printable robots are being used by students carrying out final projects for Bachelor and Master degrees. The online resources show many of these activities in action.Armesto Ángel, L.; Fuentes-Durá, P.; Perry, DR. (2016). Low-cost Printable Robots in Education. Journal of Intelligent and Robotic Systems. 81(1):5-24. doi:10.1007/s10846-015-0199-xS524811Criteria for accrediting engineering programs (Unknown Month 2015, 2014). http://www.abet.org/eac-criteria-2014-2015Board, N.S.: Moving forward to improve engineering education (2007). http://www.nsf.gov/pubs/2007/nsb07122/nsb07122.pdfCampion, G., Bastin, G., d’Andréa Novel, B.: Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. IEEE Trans. Robot. Autom. 12(1), 47–62 (1996)Carberry, A.R., Lee, H.-S., Ohland, M.W.: Measuring engineering design self-efficacy. J. Eng. Educ. 99(1), 71–79 (2010)Castro. A.: Robotic arm with 6 dof (2012). http://www.thingiverse.com/thing:30163Choset, H., Lynch, K.M., Hutchinson, S., Kantor, G.A., Burgard, W., Kavraki, L.E., Thrun, S.: Principles of Robot Motion: Theory, Algorithms, and Implementations. MIT Press, Cambridge MA (2005)d’Andréa Novel, B., Campion, G., Bastin, G.: Control of nonholonomic wheeled mobile robots by state feedback linearization. Int. J. Robot. Res. 14(6), 543–559 (1995)Denavit, J., Hartenberg, R.S.: A kinematic notation for lower-pair mechanisms based on matrices. Trans. ASME J. Appl. Mech 22(2), 215–221 (1955)Dowdall. J.: Rofi robot five (2012). http://www.projectbiped.com/prototypes/rofiEliot, M., Howard, P., Nouwens, F., Stojcevski, A., Mann, L., Prpic, J., Gabb, R., Venkatesan, S., Kolmos, A.: Developing a conceptual model for the effective assessment of individual student learning in team-based subjects. Australas. J. Eng. Educ. 18(1), 105–112 (2012)Fox, D., Burgard, W., Thrun, S.: The dynamic window approach to collision avoidance. Robot. Autom. Mag. IEEE 4(1), 23–33 (1997)Fuentes-Dura, P., Armesto, L., Perry, D.: Multidisciplinary projects: Critical points and perceptions in valladolid in innovation and quality in engineering education. In: Innovation and Quality in Engineering Education, pp 315–331 (2012)Fuentes-Dura, P., Cazorla, M.P., Molina, M.G., Perry, D.: European project semester: Good practices for competence acquisition. In: Valencia Global, pp 165– 172 (2014)González, J., Barrientos, A., Prieto-Moreno, A., de Frutos, M.A.: Miniskybot 2 (2012). http://www.iearobotics.com/wiki/index.php?Miniskybot_2Gonzalez-Gomez, J., Valero-Gomez, A., Prieto-Moreno, A., Abderrahim, M.: A new open source 3d-printable mobile robotic platform for education. In: Rckert, U., Joaquin, S., Felix, W. (eds.) Advances in Autonomous Mini Robots, pp 49–62. Springer, Berlin Heidelberg (2012)Gonzlez, J., Wagenaar, R. (eds.): Tuning Educational Structures in Europe University of Deusto and Groningen. Deusto (2003)Heinrich, E., Bhattacharya, M., Rayudu, R.: Preparation for lifelong learning using eportfolios. Eur. J. Eng. Educ. 32(6), 653–663 (2007)Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. The Int. J. Robot. Res. 5(1), 90–98 (1986)Krassman, J.: Quadcopter hummingbird ii (2013). http://www.thingiverse.com/thing:167721Langevin, G.: Inmoov (2012). http://www.inmoov.frMadox: ecanum wheel rover 2 (2011). http://www.madox.net/blog/2011/01/24/mecanum-wheel-rover-2Miles, M.B., Analysis, A.M.: Huberman. Qualitative Data: An Expanded Sourcebook. SAGE Publications (1994)Minguez, J., Montano, L.: Nearness diagram (nd) navigation: Collision avoidance in troublesome scenarios. IEEE Trans. Robot. Autom. 20, 2004 (2004)Olalla: Caterpillator v1.1 (2011). http://www.thingiverse.com/thing:8559Ollero, A.: Robótica. Manipuladores y robots móviles Marcombo, S.A. Barcelona (2001)Price, M.: Hf08 hexapod robot (2012). http://www.heliumfrog.com/hf08robot/hf08blog.htmlRawat, K., Massiha, G.: A hands-on laboratory based approach to undergraduate robotics education. In: Proceedings of 2004 IEEE International Conference on Robotics and Automation 2, pp 1370–1374 (2004)Robotics, C.: Virtual experimentation robotic platform (v-rep) (2013). www.coppeliarobotics.comScott, B.: Principles of problem and project based learning the aalborg model. Aalbord University (2010)Teichler, U., Schonburg, H.: editors. Comparative Perspectives on Higher Education and Graduate Employment and Work Experiences from Twelve Countries. Kluwer Pub. (2004)Ulrich, I., Borenstein, J.: Vfh+: reliable obstacle avoidance for fast mobile robots. In: Robotics and Automation, 1998. Proceedings, volume 2, pp 1572–1577 (1998)Verner, I., Waks, S., Kolberg, E.: Educational robotics An insight into systems engineering. Eur. J. Eng. Educ. 24(2), 201–212 (1999)C.y.A. Vicerrectorado de Estudios: Dimensiones competenciales upv (2013). http://www.upv.es/contenidos/ICEP/info/DimensionesCompetenciales.pdfWampler, C.W.: Manipulator inverse kinematic solutions based on vector formulations and damped least squares methods. IEEE Trans. Syst. Man, Cybern. 16(1), 93–101 (1986)Weinberg, J., Yu, X.: Robotics in education Low-cost platforms for teaching integrated systems. Robot. Autom. Mag. IEEE 10(2), 4–6 (2003

Duality-Based Nonlinear Quadratic Control: Application to Mobile Robot Trajectory-Following

(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] This paper presents noniterative linearizationbased controllers for nonlinear unconstrained systems, coined as extended Rauch Tung Striebel (ERTS) and unscented Rauch Tung Striebel (URTS) controllers, derived from the duality between optimal control and estimation. The proposed controllers use a Rauch Tung Striebel forward backward smoother as an state estimator to compute the original optimal control problem. The new controllers are applied to trajectory-following problems of differential-drive mobile robots and compared with iterative linear quadratic regulator controller, nonlinear model predictive control, and approximate inference approaches. Simulations show that ERTS and URTS controllers produce almost optimal solutions with a significantly lower computing time, avoiding initialization issues in the other algorithms (in fact, they can be used to initialize them). This paper validates ERTS controller with an experiment of a Pioneer 3-DX mobile robot.This work was supported in part by the PrometeoII/2013/004 through the Generalitat Valenciana, in part by the Spanish Government under Project DPI2011-27845-C02-01, in part by the VALi+d Program through the Generalitat Valenciana, in part by the European Regional Development Fund through the Ministry of Education, Youth and Sports, Czech Republic, under Project CZ.1.05/2.1.00/03.0094, in part by the Regional Innovation Centre for Electrical Engineering, and in part by the Czech Science Foundation under Project GACR P 102/11/0437. Recommended by Associate Editor A. G. Aghdam.Armesto Ángel, L.; Girbés, V.; Sala, A.; Miroslav Zima; Václav mídl (2015). Duality-Based Nonlinear Quadratic Control: Application to Mobile Robot Trajectory-Following. IEEE Transactions on Control Systems Technology. 23(4):1494-1504. https://doi.org/10.1109/TCST.2014.2377631S1494150423

Haptic Feedback to Assist Bus Drivers for Pedestrian Safety at Low Speed

Buses and coaches are massive Passenger Transportation Systems (PTS), because they represent more than half of land PTS in the European Union. Despite of that, bus accident figures are lower than other means of transport, but its size and weight increase the severity of accidents in which buses are involved, even at low speed. In urban scenarios, turnings and manoeuvres around bus stops are the main causes of accidents, mostly due to low visibility, blind spots or driver s distractions. Therefore, there is an increasing interest in developing driving assistance systems to avoid these situations, among others. However, even though there are some solutions on the market, they are not meant to work in urban areas at low speed and with the sole purpose of preventing collisions with pedestrians. In this sense, the paper proposes an active safety system for buses in manoeuvres at low speed. The safety system consists of haptic feedback devices together with collision avoidance and risk evaluation systems based on detected people nearby the bus. The performance of the active safety system has been validated in a simulated urban scenario. Our results show that driver s reaction time is reduced and time to collision increased due to the proposed low-speed active safety system. In particular, it is shown that there is a reduction in the number of high risk cases and collisions, which implies a considerable improvement in safety terms. In addition to this, a brief discussion about current regulations for innovative safety systems on a real vehicles is carried out.This paper has been funded by Ministerio de Ciencia e Innovacion (Spain) through the projects "Sistemas Avanzados de Seguridad Integral en Autobuses (SAFEBUS)" (IPT-2011-1165-370000) and "Sistemas de Conduccion Segura de Vehiculos de Transporte de Pasajeros y Materiales con Asistencia Haptica/Audiovisual e Interfaces Biomedicas (SAFETRANS)" (DPI2013-42302-R). This work was also supported by Programa VALi+d (Generalitat Valenciana). The authors wish to thank Jose Luis Sanchez Carrascosa for his dedication and commitment to the project and thank to Ana Isabel Sanchez Galdon for her valuable help regarding ANOVA analysis.Girbés, V.; Armesto Ángel, L.; Dols Ruiz, JF.; Tornero Montserrat, J. (2016). Haptic Feedback to Assist Bus Drivers for Pedestrian Safety at Low Speed. IEEE Transactions on Haptics. 9(3):345-357. https://doi.org/10.1109/TOH.2016.2531686S3453579

An Active Safety System for Low-Speed Bus Braking Assistance

Accidents in which buses or coaches are involved cause thousands of injuries and fatalities every year. To reduce their number and severity, the paper describes an Advanced Driver Assistance Systems (ADAS) based on a haptic throttle pedal and emergency braking. It also proposes a computationally efficient algorithm with a methodology based on three main concepts: a simplified but accurate vehicle model; an efficient collision detection system considering driver's intention and pedestrians wandering around the vehicle; and a risk evaluation system to generate warnings and emergency braking signals. Finally, the performance of the proposed ADAS is validated using a driving simulation cabin with a very realistic urban scenario and original elements from real buses. The results show a statistically significant improvement in safety, as the number of collisions and high risk situations are clearly minimized, reaction time to press the brake pedal is improved and time to collision increased in emergency situations. Implementation of the proposed ADAS into city buses would potentially improve safety, reducing the frequency and severity of accidents with pedestrians.This work was supported in part by Ministry of Science and Innovation of Spain through the SAFEBUS Project "Sistemas Avanzados de Seguridad Integral en Autobuses" under Grant IPT-2011-1165-370000 and the SAFETRANS Project "Sistemas de Conduccion Segura de Vehiculos de Transporte de Pasajeros y Materiales con Asistencia Haptica/Audiovisual e Interfaces Biomedicas" under Grant DPI2013-42302-R and in part by the Generalitat Valenciana, Programa VALi+d (ACIF/2010/206). The Associate Editor for this paper was E. Kosmatopoulos.Girbés, V.; Armesto Ángel, L.; Dols Ruiz, JF.; Tornero Montserrat, J. (2017). An Active Safety System for Low-Speed Bus Braking Assistance. IEEE Transactions on Intelligent Transportation Systems. 18(2):377-387. https://doi.org/10.1109/TITS.2016.2573921S37738718

Advanced Driving Assistance Systems for an Electric Vehicle

This paper describes the automation of a Neighborhood Electric Vehicle (NEV) and the embedded distributed architecture for implementing an Advanced Driving Assistance System (ADAS) with haptic, visual, and audio feedback in order to improve safety. For the automation, original electric signals were conditioned, and mechanisms for actuation and haptic feedback were installed. An embedded distributed architecture was chosen based on two low-cost boards and implemented under a Robotics Operating System (ROS) framework. The system includes features such as collision avoidance and motion planning.Muñoz Benavent, P.; Armesto Ángel, L.; Girbés Juan, V.; Solanes Galbis, JE.; Dols Ruiz, JF.; Muñoz, A.; Tornero Montserrat, J. (2012). Advanced Driving Assistance Systems for an Electric Vehicle. International Journal of Automation and Smart Technology. 2(4):329-338. doi:10.5875/ausmt.v2i4.169S3293382

CoppeliaSim (V-REP): Introduction

In this video, we introduce the use of CoppeliaSim softwarehttps://polimedia.upv.es/visor/?id=af842180-3851-11ea-a1bf-2d6b581c769aArmesto Ángel, L. (2021). CoppeliaSim (V-REP): Introduction. http://hdl.handle.net/10251/167272DE

CoppeliaSim (V-REP): Creación de gráficas

Este vídeo explica cómo crear gráficas en CoppeliaSimhttps://polimedia.upv.es/visor/?id=5484ba30-4f1a-11ea-b7d9-832cbebadcfbArmesto Ángel, L. (2020). CoppeliaSim (V-REP): Creación de gráficas. http://hdl.handle.net/10251/145628DE

Sistemas robotizados. Matriz de rotación

Este vídeo explica el uso de las matrices de rotación para la representación de la orientación en el espacio 3D.https://polimedia.upv.es/visor/?id=1b06f390-41c3-11ea-b5a8-4b6b44532450Armesto Ángel, L. (2020). Sistemas robotizados. Matriz de rotación. http://hdl.handle.net/10251/145452DE

DYOR: Cómo implementar seguilíneas

Este vídeo explica cómo implementar un algoritmo para el seguimiento de líneas con un sensor TCRT5000 para robots de bajo coste.https://polimedia.upv.es/visor/?id=5b15d4e0-2716-11e6-bb62-f1c4f1c8a57eArmesto Ángel, L. (2021). DYOR: Cómo implementar seguilíneas. http://hdl.handle.net/10251/167446DE