基于麦克纳姆轮的全方位机器人移动底盘的设计【原创含9张CAD图带答辩ppt+外文翻译】
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基于麦克纳姆轮的全方位机器人移动底盘的设计【含9张CAD图带答辩ppt+外文翻译】
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研究概述,研究方法,设计简述,麦克纳姆轮移动底盘设计毕业答辩,学号：,指导老师：,XXXX,XXXXX,答辩人：,XXXX,班级：,XXX,论文结构,具体讲述,毕设感悟,基于McNaum轮的全方位移动底盘具有出色的移动性能, 并且可以在任何方向上进行移动，而无需底盘进行旋转运动。所以它的应用场合是十分多的，比如在空间狭小的环境和在物流运输中运用。本次论文设计了一种可行的Mecanum轮设计方案,并基于Mecanum轮的全向移动底盘建立了运动学理论模型,它为全面的移动底盘控制算法提供了理论的基础。基于此，自主设计和开发了基于Mecanum轮的全方位移动底盘。,“,”,研究概述,研究方法,设计简述,论文结构,具体讲述,毕设感悟,研究方法,设计简述,1,2,3,研究,研究目标,研究意义,研究的问题,机构以轮式结构进行运动，可以在比较平整的路面进行正常的工作并能实现全向运动。,对移动底盘总体进行设计，对重要零部件进行创新,主要研究的问题有：设计较为优质的移动底盘主体结构、主要参数的选择与计算,研究概述,论文结构,具体讲述,毕设感悟,1,2,3,查阅资料了解麦克纳姆轮移动底盘相对于其他形式移动底盘的优势。,调研现在市场上主流的移动底盘的结构形式，了解其优点与不足。,针对了解的资料设计主体结构，并对主要不足零部件进行优化。,研究概述,研究方法,设计简述,论文结构,具体讲述,毕设感悟,研究方法,具体讲述,专题,主体,论文,参数,传动,设计简述,论文结构,研究概述,毕设感悟,研究背景,研究方法,研究结果,问题讨论,毕设感悟,论文绪论,A,B,C,感悟一,感悟二,感悟三,本次毕设是对我大学学习的考验，各种理论与实践综合运用，是一次突破自我的挑战。,对机器各个部件全方位的设计，包含的知识点众多，需要考虑为问题繁多，充分锻炼了我的细心程度。,做事需懂得协作，在做毕设过程中遇到了很多难解的问题，在导师与同学的帮助下得到了准确快速的解决。,感谢聆听,答辩人：,指导老师：,XXXX,XXXX,8th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2017 The Control System Based on Extended BCI for a Robotic WheelchairTimofei I. Voznenko_, Eugene V. Chepin, and Gleb A. Urvanov National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) Moscow, Russia Abstract In most cases, the movement of wheelchairs is controlled by disabled people using a joystick or by an accompanying person. Significantly disabled patients need alternative control methods without using the wheelchair joystick because it is undesirable or impossible for these patients. In this article, we present the implementation of a robotic wheelchair based on a powered wheelchair that is controlled not by the joystick but by the onboard computer that receives and processes data from the extended brain-computer interface (extended BCI). Under this term we understand the robotic complex control system with simultaneous independent alternative control channels. In this robotic wheelchair version the BCI works with voice and gesture control channels. Keywords: extended brain-computer interface, robotic wheelchair, control channel, robotics 1 Introduction Technical projects on the development of robotic wheelchairs have been carried out since the last century. Modern mobile robotic complexes (MR) which include robotic wheelchairs are complex heterogeneous hardware and software systems and they should provide a certain level of comfort and reliability of control answering the fields of their application. Under the term MR we understand the robotic system having an onboard powerful, versatile, and inexpensive miniature computer with a modern CPU providing the ability to connect the modern peripherals to the system without any restrictions, unlike the microcontroller capabilities. Because of this, it is possible to use the maximum possible set of software, more memory and parallel programming techniques to achieve the real-time mode (RTM).The robotic wheelchair (hereinafter the “chair”) is designed for patients with severe disorders of the musculoskeletal system and other functions of the body (hands, speech, hearing, etc.). The patient is the operator of the chair sitting in it and controlling it via the control system. For clarity we will call them the “patient”. Along with it, the chair is controlled by the specialistoperator who can remotely monitor the chair. This is possible because of a parallel chair-control channel provided by the Wi-Fi connection of the onboard computer with a remote Tracking and Control Station (TCS). TCS is a remote computer through which the specialist-operator can control the chair “intercepting”, if necessary, the control from the patient-operator.2 Related WorksThe patients who use the wheelchairs in most cases are quite satisfied with them, if the chair is equipped with an electric drive and control system via the joystick. An example of such a robotic wheelchair called Wheelesley is described by Yanco 1. This chair provides additional opportunities for the patient during the driving by the provision of the information “with a lower level of navigation”.One of the modern trends in the development of the robotic wheelchairs is the projects such as the Chinese project Chiba (Robotic wheelchair) described by Morales et al. 2 and Szondy 3. The main objective of these projects is the control system of the mechatronics of the chair which effectively overcomes the obstacles in the way such as stairs and border stones. However, some patients are unable to control the chair with such functions. Therefore, for these patients the way to improve the quality of their lives is the development of the control systems for the robotic wheelchairs that would allow them to control their own wheelchair using their modest possibilities: weak hands, voice, etc.There is a great variety of the ways to control the MR. The most common is to control directly by the joystick as described by Jawawi et al. 4. However, the directly connected to the servomotor of the joystick Arduino opens the opportunity of controlling the chair using such methods as the brain-computer interface (BCI), voice or gesture control. Each MR has onboard a powerful general-purpose computer. It interacts during the operation with the external computing unit Tracking and Control Station (TCS). The TCS allows to carry out the remote control of the MRs work by the operator. Also, it is possible to send to the TCS the data to gather the statistics on the basis of which it is possible to make the changes in the values of the parameters to improve the quality of the MRs control. The global problem of increasing the intelligence of such complex systems is extremely relevant nowadays, especially in the transition to the control of the teams of robots, for example proposed by Bereznyak et al. 5. For some applications of the MRs their control circuit includes a human-operator. For example, in medicine it is extremely important to implement the control system based on the traditional paradigm of “control commands”, but on the basis of non-traditional methods of controlling the complex systems. There are several works describing BCI-controlled wheelchairs but the control accuracy is not high enough for reliable control, for example, 50% and above described by Ng et al. 6 and 79.38% presented by Achic et al. 7. In order to increase the control accuracy of BCI-controlled robotic wheelchair we propose using of other control channels like voice commands or gestures. In this project, we proposed the new non-traditional control method we called “extended BCI”, which involves the operation of three control channels in parallel: voice commands, gestures and the BCI. The urgency and necessity of this control method is determined by the field of its application: medical robotics.3 Theory 3.1 The Nontraditional Methods of MR Control Under the traditional method of MRs control we understand the way to control using the commands passed from the operator to the MRs control system via some interface. Under the non-traditional control methods we understand in this article the following: BCI, voice control, control with gestures. The BCI is an interface that provides a direct transmission of the information from the brain to the computing device as described by Tromov and Skrugin 8. Recently different companies has developed the portable BCI such as NeuroSky, MindFlex, Emotiv, as described by Stamps and Hamam 9. Some of these neurocomputing interfaces allows not only to obtain the EEG (electroencephalogram) data, but also to obtain data about the emotional state of the operator, for example used by Chepin et al. 10 and Voznenko et al. 11. The voice control is a way of interaction between a man and a computer by the voice. This method of control is based on the processing of audio signals coming from a microphone. Speech recognition system using phonemes and grammar follows Lamere et al. 12. The gesture recognition system was developed by Chistjakov et al. 13 in the “Robotics” laboratory of the NRNU MEPhI. The algorithm determines the fact of the hand getting in the graphics region (specified area) corresponding to a particular gesture. This system is installed into the wheelchair to control its movement by the hand gestures and finger movements of the patient. 3.2 Extended BCI The main scientific and engineering idea of the described project is the development of the control system. The general ideology of the project is based on the concept of “extended BCI” proposed by Tromov and Skrugin 8, Dyumin et al. 14, Chepin et al. 15 and Urvanov et al. 16, by which we mean the presence in the control system the following robot-control channels: BCI, voice control, control with gestures.The term “extended BCI” was introduced in order to emphasize that in addition to the control channel based on the parallel BCI there are other ones, not so common channels. BCI is the main control method, but in practice there are situations when a particular patient more effectively controls the wheelchair using the voice commands and/or gestures. With this approach, it is necessary to solve the problem of choosing the most correct control channel. In addition, the architecture should implement the possibility of taking into account the disease peculiarities of the particular patient and develop a decision-making mechanism based on the analysis of the information from all control channels. 3.3 The Task of Decision-Making The concept of “extended interface” includes several different control channels of the MR by the operator. The general scheme of the decision-making system based on the data from the extended BCI interface is presented in Figure 1. When using more than one data channel to control the MR it is needed to solve the problem of the decision-making. In general, the problem looks as follows: there are several control channels and it is necessary to decide what command should be executed at a given time. The decision-making system should have the following features: 1. To be deterministic. If we know the specificity of working with the extended BCI-interface system components it is possible to make the deterministic decision-making system taking into account the mentioned features of the components. 2. The ability to have the varying credibility degree for the control system channels . Since the channels have different degree of credibility, it is logical that the information coming to the decision-making system should have the different values. 3. Support an asynchronous data input. Despite the fact that the part of the data is received synchronously and during a long period of time, the solutions based on asynchronously incoming information having a greater relative value should be taken timely. 4. Work with continuous processes. For example, when working with thought-images it is important to record not only the state but also the dynamic characteristics of the process, and the previous state. Thus, the developed method of decision-making should be similar to the automaton with a memory. The decision-making system prototype satisfying all requirements was implemented using channels accuracy based priority accounting.Figure 1: General problem statement4 ImplementationThe current “chair” hardware-software complex consists of:1. The wheelchair with the electric drive “Titan” LY-103-120, which is designed for the independent movement in the premises and on roads with hard-surface for the disabled people with diseases of the musculoskeletal system and injuries of the lower extremities (Figure 2a). Instead of joystick control the chair has a control unit, which has an interface with the onboard computer port.2. The neural interface on the basis of the Emotiv Epoc (Figure 2b) and the software module. The Emotiv Epoc BCI allows one to obtain information not only about the fact that the user thought about the thought-images, but also the quantitative assessment of this fact (power).b)a) c)Figure 2: a) The “chair”, b) BCI Epoc Emotiv, c) Intel RealSenseChannel 1Channel 2Channel 3Channel N。 。 。 。 。 。 。DecisionMakingSystemControlSignal3. The basic equipment for the operator video interface with the robot for the development of a system of gesture recognition (a stereo camera for fixing the movements and gestures of the operator and the set of individual cameras). The arm tracking is made using an Intel RealSense camera that is shown in Figure 2c. 4. The basic equipment for the operator audio interface with the chair. The voice recognition takes place with the help of English phonetics of the Sphinx-4 library developed by Lamere et al. 12. The dictionary consists of the words matched the available phonetics 5 Results and Conclusion The “chair” project has received quite a wide coverage in Russian and the foreign mass-media: a few reports on some Russian TV-channels, in particular, on the NTV 17, as well as in the press of Spain and Spanish-speaking countries, for example in El Diario de Hoy 18, El Universal 19 and in China (Science and Technology Daily 20). Acknowledgments We would like to thank the RFBR for support of this project by the grant No. 14-07-00843 “The intelligent robotic wheelchair”. References 1 H. A. Yanco. Wheelesley: A robotic wheelchair system: Indoor navigation and user interface. In Assistive technology and artificial intelligence, pages 256268. Springer, 1998.2 R. Morales, A. Gonzalez, V. Feliu, and P. Pintado. Environment adaptation of a new staircase-climbing wheelchair. Autonomous Robots, 23(4):275292, 2007.3 D. Szondy. Chiba robotic wheelchair turns wheels into legs. Gizmag, October 17, 2012, , 2012. 4 D. N. Jawawi, K. Kamal, M. A. S. Talab, M. Z. M. Zaki, N. M. Hamdan, R. Mohamad, R. Mamat, and S. Sabil. A Robotic Wheelchair Component-Based Software Development. INTECH Open Access Publisher, 2011. 5 5 I. S. Bereznyak, E. V. Chepin, and A. A. Dyumin. The actions language as a programming frame-work for cloud robotics applications. In Cloud System and Big Data Engineering (Confluence), 2016 6th International Conference, pages 119124. IEEE, 2016. 6 D. W. K. Ng, Y. W. Soh, and S. Y. Goh. Development of an autonomous bci wheelchair. In Computational Intelligence in Brain Computer Interfaces (CIBCI), 2014 IEEE Symposium on, pages 14. IEEE, 2014.7 F. Achic, J. Montero, C. Penaloza, and F. Cuellar. Hybrid bci system to operate an electric wheelchair and a robotic arm for navigation and manipulation tasks. In Advanced Robotics and its Social Impacts (ARSO), 2016 IEEE Workshop on, pages 249254. IEEE, 2016. 8 A. G. Trofimov and V. I. Skrugin. Brain-computer interfaces. review. Information Technologies, (2):211, 2011. 9 K. Stamps and Y. Hamam. Towards inexpensive bci control for wheelchair navigation in the enabled environmenta hardware survey. In International Conference on Brain Informatics, pages 336345. Springer, 2010. 10 E. V. Chepin, A. A. Dyumin, G. A. Urvanov, and T. I. Voznenko. The improved method for robotic devices control with operators emotions detection. In NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW), 2016 IEEE, pages 173176. IEEE, 2016.11 T. I. Voznenko, G. A. Urvanov, A. A. Dyumin, S. V. Andrianova, and E. V. Chepin. The research of emotional state influence on quality of a brain-computer interface usage. Procedia Computer Science, 88:391396, 2016.12 P. Lamere, P. Kwok, E. Gouvea, B. Raj, R. Singh, W. Walker, M. Warmuth, and P. Wolf. The cmu sphinx-4 speech recognition system. In IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2003), Hong Kong, volume 1, pages 25, 2003. 13 I. S. Chistjakov, G. A. Urvanov, D. V. Bajkov, and E. V. Chepin. Sistema upravlenija robo-tizirovannym kreslom pri pomoshhi zhestov (the system of control robotic wheelchair using ges-tures). Vestnik natsionalnogo issledovatelskogo yadernogo universiteta “MIFI”, 5(4):381388, 2016.14 A. A. Dyumin, P. S. Sorokoumov, E. V. Chepin, and G. A. Urvanov. Architecture and prototype of human-machine interface with mobile robotic device. Vestnik natsionalnogo issledovatelskogo yadernogo universiteta “MIFI”, 2(3):376380, 2013. 15 E. V. Chepin, A. A. Dyumin, P. S. Sorokoumov, and G. A. Urvanov. A prototype of the brain-computer interface for mobile robot. In The 15th International Workshop on Computer Science and Information Technologies (CSIT 2013), volume 2, pages 202206. CSIT, 2013.16 G. A. Urvanov, V. V. Danshin, A. A. Dyumin, and Chepin E. V. The system of human interaction as an agent of mobile robotic system. Software systems and computational methods, (1):4551, 2015. 17 V moskve ispytali invalidnoe kreslo, upravljaemoe siloj mysli (in moscow was experienced a wheelchair controlled by thought). http:/www.ntv.ru/novosti/1604180/, 2016. 18 La silla de ruedas del futuro sera guiada por el pensamiento y las emociones (the wheelchair of the future will be guided by thought and emotions). /articulo/internacional/ silla-ruedas-del-futuro-sera-guiada-por-pensamiento-las-emociones-109909, 2016. 19 La silla de ruedas del futuro sera guiada por el pensamiento (the wheelchair of the fu-ture will be guided by thought). /noticias/estilo-vida/ sill
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