KAIST Interactive Bicycle Simulator

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1 Proceedings of the 2001 IEEE International Conference on Robotics & Automation Seoul, Korea May 21-26, 2001 KAIST Interactive Bicycle Simulator Dong-Soo Kwon, Gi-Hun Yang, Chong-Won Lee, Jae-Cheol Shin, Youngjin Park, Byungbo Jung, Doo Yong Lee, Kyungno Lee, Soon-Hung Han, Byoung-Hyun Yoo, Kwang-Yun Wohn *, Jung-Hyun Ahn * Department of Mechanical Engineering, * Department of Computer Science Korea Advanced Institute of Science and Technology Taejeon, , Korea kwonds@me.kaist.ac.kr Abstract This paper presents key technologies and system integration issues of the KAIST interactive bicycle simulator. The rider on the bicycle feels the motion and has the visual experience as if he/she is riding in the campus of the Korea Advanced Institute of Science and Technology. The simulator consists of a bicycle, a Stewart platform, a Magneto-Rheological handle and a pedal resistance system to generate motion feelings; the real-time visual simulator and the projection system; the sub-controllers and the integrating control network. 1. Introduction Various vehicle simulators such as automobile, bicycle, flight, tank and ship simulators have been developed and are becoming widely used for the testing of design, evaluation of environments, training for driving, entertainment and so on[1]. Even though many papers have been presented regarding various riding simulators, there are few related to two-wheeled and human-powered simulators such as a bicycle simulator. The bicycle simulator has been one of the most challenging simulators to develop because of the inherent unstable dynamics of the bicycle that are coupled with the human rider s dynamics. The real time simulation of human-controlled and human-powered vehicles moving in a virtual environment is a very challenging problem that has just been tackled. The Max-Plank institute has developed a bicycle simulator that consists of a visual simulator with a large truncated cone-shaped projection screen and a simple motion generation system[2]. Carnegie Mellon University has also made an elementary bicycle simulator using a head mounted display(hmd) and a simple pedaling device[3]. Lately, Nanyang University has developed a bicycle simulator using a 6-dof Stewart platform, an HMD and a force feedback system[4]. We also developed a bicycle simulator to study essential issues and integration technologies in order to develop more advanced interactive simulators. It has been named the KAIST interactive bicycle simulator as the visual environment of the simulator is based on the KAIST campus. This paper introduces the motion generation system, the bicycle dynamics, the handlebars and pedal resistance systems, the visual simulator, and the system integration technique, which are essential technologies of the KAIST interactive bicycle simulator. 2. Motion Generation System and Bicycle Dynamics 2.1 Components of the Bicycle Simulator The system consists of a motion generation system consisting of the Stewart platform to provide 6-dof motion to the bicycle, handle and pedal resistance systems which are attached to the handlebars and the rear wheel, respectively; the visual simulator to create dynamic images, and three computers. Regarding the signal flow of the bicycle simulator, a rider gives the input force/torque to the bicycle in response to some circumstance given by the visual simulator and then the handlebar and pedal resistance systems measure the handlebar angle, pedaling torque or braking torque and the motion platform estimates the rider s tilting motion. After that, the obtained data are transferred to the bicycle dynamics module. The dynamics module calculates the location and the velocity of the bicycle and some reactive forces. The visual and motion cues and reactive forces made in each system are fed back to the rider. Fig 1 shows motion generation and the handle/pedal systems. 2.2 Motion Generation System A 6-dof Stewart platform, which consists of 6 linear actuators and upper and lower platforms, is used for the bicycle motion generation system. The Stewart platform, which is driven by an electrical through a ball screw is designed with a load capability of 130kgf. This is adequate for the motion generation system of the bicycle simulator. The tracking control performance of the system should be up to 7Hz in frequency to simulate real bicycle /01/$ IEEE 2313

2 motion. To do this, we used a model-based control strategy that requires calculation of the system dynamics at every sampling time. As calculation of the Stewart platform dynamics, including the numerical forward kinematics, is a heavy computational burden for high speed motion control, two processors for digital servo control of the Stewart platform have been employed, consisting of a PC and DSP interfaced to the PC bus. The two processors communicate with each other through a dual port RAM installed in the DSP board so that digital data are transferred at a high speed[5]. we used the Newton-Euler method. Twenty-four unknown parameters including the rear wheel position, the steering angle, the angular positions of the front and rear wheels relative to the handle fork and the frame, some internal forces and some angles for coordinate transformations can be calculated by the same number of established equations through the method. We consider forces such as the air drag and tire frictions in the bicycle model. At low speed, the air drag and rolling resistance is so small that they can be neglected. But at high speed, air drag is much greater than rolling resistance, so it cannot be neglected[6]. Thus, air drag, which is proportional to the square of the speed, is considered in the bicycle dynamics. We assume that the bicycle wheel tire can only deform when it makes contact with the ground. There can be many contact points between the tire and the ground. At each contact point, we model the tire as a spring-damper system and consider longitudinal, cornering and camber forces. The cornering and camber forces are generated when there exists a slip angle which is an angle between the direction of the wheel heading and the direction of travel, and the camber angle, which is an angle between the wheel and the vertical plane[7]. The derived bicycle dynamics are verified through Flush 3-D graphic animation by comparing them with real bicycle motion. 3. Display of steering reaction forces of bicycle Fig.1. The motion generation and the handlebar/pedal systems 2.3. Bicycle Dynamics Since the bicycle is a two-wheeled vehicle, it can move in a wide range of rotational directions as well as translational directions, so we should inevitably consider many degrees of freedom. To calculate the bicycle dynamics, the rider s motion and several important forces should be estimated. In this paper, the bicycle model consists of a front wheel, a rear wheel, a frame and handlebars. We assume that the mass of the whole bicycle system is concentrated on the two wheels equivalently, that is, the masses of the frame and the handlebars are distributed evenly between the two wheels. We also assume that all components except the wheel tires are absolutely rigid, that a rider can speed up and down by pedaling and braking and that the rider can change direction using the handlebars and by tilting his/her body. For the motion equation of the bicycle model, MR clutch There are two types of reaction forces from the bicycle handlebars, active and passive reaction forces. This section introduces a device for the steering reaction force system which has a and a MRF(MagnetoRheological Fluid) based clutch. This device is called the MR clutch. The MR clutch and the are used to generate the reaction force. The MR clutch and the are connected to the bicycle handlebars in series as shown in Fig. 2. The system can generate not only active reaction force but also passive reaction force. bicycle handle connection shaft MR clutch connection shaft blade MRF MR clutch controller housing controller

Fig. 2. Schematic diagram of the force reaction system with the MRF and In order to generate the active reaction force, the is running and the MR clutch transmits the power to the handlebars.

3 Fig. 2. Schematic diagram of the force reaction system with the MRF and In order to generate the active reaction force, the is running and the MR clutch transmits the power to the handlebars. To generate the passive reaction force, the is electrically or mechanically stopped and the MR clutch acts as a damper. In both cases, the magnitudes of the reaction forces are regulated by the input current applied to the MR clutch. As presented in Fig. 2, the is not rigidly connected to the operating part in contrast to the conventional -only systems and the magnitude of the reaction force transferred to the handlebars is controlled by the current applied to the MR clutch. With such an active reaction force generation, the is not prone to heat damage because most of the heat from the mechanical energy can be dissipated by the MR damper. 3.2 Application to the bicycle simulator The major design goals established for the MR clutch in the steering system of the virtual bicycle simulator are as follows : 1) the maximum dissipated torque is approximately 5Nm. 2) control frequency is up to 2Hz. The used with the MR clutch is a brushless DC, and is directly attached to a geared. The and the MR clutch are attached to the bicycle simulator as shown in Fig. 3. M R clutch bicycle body Jig 1 MR clutch Jig 3 Jig 2 Jig 4 geared Fig. 3. Installation of the handlebar force reaction system 4. Control of Pedal resistance system Since only the rear wheel is accelerated by the rider s torque in the bicycle simulator, it is possible for the rider to feel less resistance than the resistance of the real road. So as to create a realistic sensation, pedal resistance control system generates road friction, air resistance and the resistance equivalent to the rider s inertia. The pedal resistance control system is made to generate active-torque because the acceleration effect is needed when the bicycle goes downhill. In the pedal resistance system, we estimate the torque that the rider gives to the pedal and control the spinning velocity of the simulator equivalent to the velocity calculated from the bicycle dynamics module. The pedal resistance system consists of an AC-servo, a wheel, and a MR-brake as shown in Fig.4. The generates acceleration effect due to gravity in going downhill and the MR-brake generates the resistance torque. The MR-brake can generate large resistance torque with low power compared with other active devices. If we want to generate the resistance force by a only, the should have a large torque capacity, and a heat dissipation problem may arise. Therefore the system is designed as a and MR-brake connected in parallel. A design requirement is that the system can speed up to 70km/h and generate a torque that does not allow the rear wheel to rotate when a rider exerts a force equal to half of his/her weight to the pedals. Based on this condition we designed a pedal system that can speed up to 79km/h and bear a half of a common person s weight. This pedal system is located between the Stewart platform and the rear wheel of the bicycle. Control of the pedal resistance system consists of a velocity control part and a user torque estimator as shown in Fig.5. The velocity control part calculates the velocity error control torque using the desired velocity obtained from the bicycle dynamics. In the case that this torque is positive, the generates the torque; in the case that this torque is negative, the MR-brake generates the torque. The user torque estimator estimates the torque that a rider gives to the pedal and transfers this value to the input of the bicycle dynamics. The dynamics of rear wheel can be expressed as... + c θ = τ Motor + τ MR Brake I θ + τ I is the inertia of the pedal system and c is the damping coefficient. τ Motor, τ MR-Brake and τ User are the torques of the, the MR-brake and the rider. Since we measure the rear wheel s speed, and know τ MR-Brake and τ Motor from the previous sampling step, the rider s torque can be estimated as τ User.. User τ Motor + τ MR Brake ) + I θ +. (1) = ( c θ (2) With τ user, the bicycle dynamics calculates running velocity in the virtual road, θ &. The velocity controller ref makes the simulator follow theθ & ref. Therefore, the rider feels dynamics of the bicycle model. 2315

Visual information plays an important role in perceiving objects. Especially, in a virtual environment, visual information is the major factor that allows users to be immersed into the virtual world.

4 AC Servo W heel Fig 4. Pedal resistance control system MR- Brake Fig 5. Block diagram of pedal resistance control 5. Visual Simulator The visual simulator creates dynamic images for the simulator, and visually expresses the virtual world in which the user travels. Visual information plays an important role in perceiving objects. Especially, in a virtual environment, visual information is the major factor that allows users to be immersed into the virtual world. The visual information of the virtual environment increases the realism of the simulator Campus Modeling For the campus model, geographical features and buildings are modeled separately. We scanned a 1:5000 map of KAIST made by the National Geography Institute as a raster image, and modeled roads and geographical features based on it. In the early stages, we took the altitude, latitude, and longitude information from scanned raster images at MGE, I/RAS B, I/GEOVEC which are based on MicroStation. Geographical features on the conventional maps are converted into Mercator projection. The corrections of altitude and latitude to I/RAS B are unavoidable and I/GEOVEC modified the 2D map information into a set of 3D polygons by adding the height of contour lines. Because the altitude and latitude information are mandatory, the final model does not contain these data. To model buildings, we changed dxf format into 3ds format and 3ds format is handled by MultiGen Creator. MultiGen Creator is a graphics tool for real-time 3D database development. Because it makes a database of each object, we can easily realize real-time rendering [8]. Also it shares the OpenFlight format with the real-time rendering tool, Vega. OpenFlight provides features with which we can optimize the databases for real-time simulation. To aid real-time simulation, unnecessary detailed information, not seen by the observer, is removed from MultiGen Creator. For realism, photographic pictures were used as texture. However, more weight is given to the real-time rendering over the quality of images Implementation of the Visual Simulation To realize real-time simulation, we can use a commercial tool such as WorldToolKit or Vega.Our system uses the commercial product Vega and an application called Kitten that has been developed by KAIST. Vega provides a graphic user interface called LynX. We can add basic functions such as adding an object, constructing scenes, changing graphic status, setting windows and channels, selecting motion, making a navigation path, and setting the light source [9]. Additional functions can be implemented using Vega APIs for complex simulation. Because creating the visual images of the simulator requires a massive calculation unlike other systems, we need fast processors and more memory[10]. A rider manipulates the input devices of the bicycle such as the handlebars, pedals, and brakes. With the rider s input and the geographical information from the visual database, the bicycle dynamics can calculate the location of the bicycle. The visual simulator creates images from the calculated location. Fig. 6 shows the campus model using Vega. Fig. 6. Example image of the campus model with Vega The visual simulator obtains the front and the rear wheel information from the bicycle dynamics in addition to the user location for image creation. Then it gives geographical information like the contact points of the wheels with the ground, normal vectors, and type of ground condition (asphalt, blicks, grass and so on) to the bicycle dynamics. The data exchange between the visual simulator and the bicycle dynamics system continues as 2316

the simulator works. 5.3. Display A rider can see the created images with a beam projector or an HMD (Head Mounted Display).

5 the simulator works Display A rider can see the created images with a beam projector or an HMD (Head Mounted Display). Image projection methods can be divided into two types by usage and method, the front projection and back projection. Each type can be divided into mono or stereo (3D) projection. Because of space restrictions and budget limits, front mono projection has been used in this study. Stereo projection is not adopted because of the optical characteristics of screen and the limitation of space. In addition to the beam projector, we tested the visualization using an HMD. The distinguishing features of an HMD are that with a tracking sensor, we can follow the motion of a user s head. In addition to the stereo 3D image [11], HMD saves space and reflects the motion of the user s head. 5.4 Visual Simulator(Kitten) Typically, a virtual reality system consists of the simulation module and the rendering module. If these two modules are put in a single loop, the performance of the system is likely to be sensitive to the individual module. For example, the frame rate will slow down when the virtual world involves complex physical simulation, even if its visual complexity is rather low. Ideally, simulation should make no effect on the system performance as a whole. Also, it is desirable that the system performance is as independent as possible to the visual complexity of the underlying scene. We have developed Kitten, a general-purpose virtual reality software, the basic design of which was focused on the complexity-independence principle described above. It is a Win9x/WinNT based API (Application Programming Interface). The structure of a typical virtual reality application, including the Kitten library, is depicted in Fig. 7. Application User Interface X-CAT Kitten Renderer Grphics Library Simulator (OpenGL, GLIDE) Fig. 7. VR system using Kitten Kitten consists of a Renderer which performs the visual and auditory rendering, and a Simulator which runs the virtual world. We use a multiple thread structure to handle the complexity-independence. For rendering, if the scene complexity increases, Renderer adjusts the number of polygons by using techniques such as scene culling, LOD (Level of Detail), and texture optimization. Virtual reality applications written in Kitten - including our bicycle simulator presented in this paper - are formed with the User Interface and X-CAT on top of Kitten. For our bike simulator, X-CAT performs collision detection, and generates the data regarding vehicle dynamics. We implemented collision detection method by using Axis- Aligned Bounding Box(AABB) and Ray-Triangle Intersection Algorithm.[12][13] User Interface module receives various 3D sensor inputs from the bicycle. Campus model run on Kitten is shown in Fig. 8. Fig. 8. Campus model using Kitten 6. System Integration The system integration focuses on the implementation of communication and synchronization among the scenes, the motion of the Stewart Platform Manipulator, and the reaction of the handlebar and pedal resistance systems. The control system of the bicycle simulator consists of three control computers: control computer I controls the Stewart Platform Manipulator; control computer II computes the bicycle dynamics and controls the handlebar and pedal resistance systems; and control computer III displays the 3D campus models. The communication between control computers I and II is realized by serial devices. Control computer II communicates with control computer III through TCP/IP protocol. Control computer II includes the dynamics process that calculates the dynamics of the bicycle; the handlebar process that controls the reactive force of the handlebars; the pedal process that controls the reactive force of the pedal resistance system; the serial process that performs the serial communication; the tcpip process that performs the TCP/IP communication; and the main process that updates the input and output signals. The input and output signals among the control computers and processes are shown in Fig. 9. The size of the signals for control computers I and III is 32 bytes and 128 bytes, respectively. 2317

6 8. Acknowledgements This work is a result of the Highly Advanced National Project(HAN Project)- Vehicle Simulator Technology for Multiusers: Bicycle Application supported by the Ministry of Science and Technology (MOST) and Virtual Reality Research Center(VRRC) of the Korea Science and Engineering Foundation (KOSEF). Fig. 9. The input and output signals among the control computers and processes. The communication protocol between control computers I and II is designed to minimize the blocked time of the control processes. Because the control process in control computer I should not be blocked to prevent the Stewart Platform Manipulator from malfunction, the signals are received by interrupt, and then sent at any time. The serial process in control computer II receives the signals from control computer I with a synchronized send/receive method. Communication protocol is designed to synchronize the 3D campus models with the calculated values of signals from the dynamics process. To minimize the blocked time in control computer III, it is important to minimize the elapsed time of the communication among the processes in control computer II. The experimental results show that it takes 0.42 ms for communication among processes in control computer II, and the elapsed time can be reduced to ms by changing the priorities of the processes. REFERENCES [1] Armando Guiso etal. Traffic simulation in the FIAT Research Driving Simulator: Development and Perspectives, DSC 95, Sophia Antipolis, France, p , 1995 [2] HartwigDistler, BicycleSimulator, n.mpg.de/bu/people/mad/projects/bicycle/bicycle.html [3] Dan Maynes-Aminzade, A Virtual Reality Bicycle Simulator, nes-aminzade.html [4] Wang Yu, Stefan Bergstrom, Lars Anderson, A True Bicyclesimulator, ww/projects_vr/bicycle_simulator/index.epl [5] Nag-In Kim, Robust motion control of Stewart platform manipulator and Its application to the vibration control of slender structure, Ph.D Thesis, KAIST [6] F. R. Whitt, D. G Wilson, Bicycling Science, The MIT press, pp.155, [7] T. D. Gillespie, Fundamentals of Vehicle Dynamics, pp.335~376, [8] Multigen-Paradigm, 1998, MultiGen Creator User's Guide [9] Multigen-Paradigm, 1997, Vega on-line user's guide [10] Roy S. Kalawsky, The science of virtual reality and virtual environment, Addison-wesley, 1993 [11] Lenny Lipton, "Stereo-vision formats for video and computer graphics," tml 7. Conclusion The KAIST interactive bicycle simulator is introduced with the system descriptions and issues of the bicycle dynamics including friction and slip between the wheel and the road, rolling and air resistances and leaning motion of a rider. The motion command is calculated from the dynamics and executed through the Stewart platform to provide a rigid body motion of the bicycle, pedal and handlebar resistance systems. Two kinds of visual simulators are used, an HMD and the projection screen. The bicycle simulator imparts a realistic feeling to the rider, with all the motions that he/she would have felt if riding in the actual KAIST campus. Currently, an advanced 2 nd version of the bicycle simulator is being developed including 3D audio sound, reduced 4- dof motion platform, and network capability. 2318

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