Volume 2013 (2013), Article ID 672826, 8 pages
Collision-Detecting Device for Omnidirectional Electric Wheelchair
Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0196, Japan
Received 9 October 2012; Accepted 1 November 2012
Academic Editors: A. Bechar, A. Sabanovic, and K.-T. Song
Copyright © 2013 Shuichi Ishida and Hiroyuki Miyamoto. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
An electric wheelchair is the device to support the self-movement of the elderly and people with physical disabilities. In this paper, a prototype design of an electric wheelchair with a high level of mobility and safety is presented. The electric wheelchair has a high level of mobility by employing an omnidirectional mechanism. Large numbers of mechanisms have been developed to realize omnidirectional motion. However, they have various drawbacks such as a complicated mechanism and difficulty of employment for practical use. Although the ball wheel drive mechanism is simple, it realizes stable motion when negotiating a step, gap, or slope. The high level of mobility enhances the freedom of users while increasing the risk of collision with obstacles or walls. To prevent collisions with obstacles, some electric wheelchairs are equipped with infrared sensors, ultrasonic sensors, laser range finders, or machine vision. However, since these devices are expensive, it will be difficult for them to be widely used with electric wheelchairs. We have developed a prototype design of collision-detecting device with inexpensive sensors. This device detects the occurrence of collisions and can calculate the direction of the colliding object. A prototype has been developed to perform motion experiments and verify the accuracy of the device. The results of experiments are also presented in this paper.
The reduced physical functions associated with aging or disability make independent living more difficult. Lower extremity function ability limits the scope to take part in vocational and educational opportunities and many also negatively affect self-esteem. If people with reduced physical functions cannot receive support, they may become bedridden. A wheelchair can compensate for a lower extremity function, by allowing users to move freely by themselves. An electric wheelchair is the device to support the self-movement of the elderly and people with physical disabilities. Previous research topics based on electric wheelchairs can be classified into projects to develop increasing a high level of mobility and projects to add intelligent functions to wheelchairs.
The conventional wheel-type mechanism needs to switch the drive when negotiating narrow spaces. An omnidirectional vehicle has no limits to its direction of motion and is expected to have a wide range of applications. Omnidirectional vehicles are an active area of research in robotics and a numerous mechanisms have been developed. To realize omnidirectional motion, vehicles so far have been equipped with an omniwheel consisting of a large number of free rollers  or a spherical ball wheel [2–5]. Several vehicles have been developed for use as electric wheelchairs . However, they must be tested for practical use.
Various input methods are used with electric wheelchairs. The traditional input method is the joystick. Voice recognition  and eye- and head-tracking [7–9] have often been used. Intelligent functions must be based on safety. However, the unintended motion of electric wheelchairs may be caused by user errors. To ensure the safety of users, many studies have focused on the avoidance of obstacles by detecting potential hazards in the local environment. The sensors that have been used by electric wheelchairs are ultrasonic sensors, infrared sensors, laser range finders, and force feedback joysticks [10–16]. In recent years, machine vision systems have been developed that use an omnidirectional camera system [17, 18], a fisheye camera system , or a stereo omnidirectional system  based on computer vision technology.
These systems cannot only help avoid collisions, but also enable the realization of additional intelligent functions such as autonomous and semiautonomous wheelchairs. However, there are still many problems to be solved. Because inexpensive and reliable systems are required in the fields of public health and welfare, as reported in this paper, we have developed an omnidirectional wheelchair with a ball wheel drive mechanism. As a measure to ensure its safety, we have also developed a collision-detecting device without expensive sensors.
2. Outline of Prototype
Photographs of the prototype are shown in Figure 1(a). The drive unit of the prototype employs a ball wheel drive mechanism with the following features: the ball wheel is a suitable shape for omnidirectional motion and do not generate vibration or noise, and a high level of ability for negotiating a step, gap, or slope. The input device of the prototype is a joystick using Arduino chipset. A battery (Ni-MH, 24 , 6.7 ) and control unit are mounted on the body. The user can move in any direction by operating the joystick.
Figure 1(b) shows the prototype collision-detecting device on the body of the vehicle. The role of this device is not to avoid collisions but to detect them. Although various types of sensors and cameras have been used to improve collision avoidance performance, it is not realistic to install these expensive devices in welfare equipment such as electric wheelchairs. We proposed a new device that can physically detect a collision and contribute to improve operation safety. Collision detection is realized by installing a bumper around the wheelchair. When the bumper collides with an obstacle, the obstacles does not come in contact with the main body of the wheelchair. The bumper can move omnidirectionally in the horizontal plane with the vehicle body. The device can calculate the collision direction from the measured displacement (position and orientation) of the bumper from the initial position. To measure the displacement, the device is equipped with three potentiometers. Moreover, so that the bumper can rerun to its initial position, the device is equipped with three tension springs and dampers. The collision-detecting device is composed of low-cost sensors.
3. Ball Wheel Drive Mechanism
We have developed a holonomic omnidirectional vehicle with a simple mechanism consisting of three ball wheels and three actuators . The layout of the mechanical parts is shown in Figure 2. Each actuator can drive two rotors simultaneously by using pulleys and belts. The rotation of each ball wheel is supported by two rollers. The mechanism does not cause overconstraint, because the number of actuators is equal to the number of degrees of freedom of motion on a flat surface.
Photographs of the prototype omnidirectional vehicle with the ball wheel drive mechanism are shown in Figure 3 and the specifications of the vehicle are shown in Table 1. The ability to negotiate more difficult terrain steps, gaps, and slopes is confirmed by motion experiments with an adult of approximately 56 kg in the wheelchair. The omnidirectional vehicle with the ball wheel drive mechanism was able to overcome a step of 14 mm, traverse a gap of 50 mm, and climb a slope of 15 deg. These abilities are necessary for practical use and allow the electric wheelchair to be used an indoor environment.
4. Collision-Detecting Device
4.1. Concept of Collision-Detecting Device
The basic part of the collision-detecting device is the frame surrounding the vehicle body. Each potentiometer in the device is arranged on the long side of the bumper and can measure different directions. A sensor unit consisting of a potentiometer, a tension spring, and a damper is installed on the frame, as shown in Figure 4(a). A rotary knob is attached to a link with a slit, as shown in Figure 5. When the bumper is moved by a collision, it causes the link to rotate around the pin. The arrangement of the link and pin is shown in Figure 4(b). Using each measurement value, the system can calculate the position and orientation of the bumper. After the collision, the bumper returns to the initial position, and the force for which is provided by a tension spring connected to the bumper and the vehicle body. To support the smooth movement of the bumper in the horizontal plane, a free caster is installed on each short side of the bumper. The free caster rotates passively on the vehicle chassis to realize the smooth motion of the bumper.
We defined the fixed coordinate of the vehicle as shown in Figure 6, in which and are the distances from the vehicle center to the pin and potentiometer, respectively. and in Figure 7(a) designate the center positions of each pin and potentiometer, respectively . First, to evaluate the motion of the bumper, we define the initial position. Define as the fixed coordinate of the bumper. In the initial condition, coincides with which is the origin of the vehicle coordinate. The rotation angles are formed by pin and the vehicle coordinate. Here, counterclockwise rotation is assumed to be positive. The positions of pin and potentiometer are as fellows: It is assumed that the bumper is moved by a collision in Figure 7(b), meaning that the fixed coordinate of the bumper is displaced relative to the vehicle coordinate (position : -axis, : -axis, orientation : ). The center of each potentiometers is given by Let be the rotation angle from the -axis to the line segment joining the pin and potentiometer center. Here, is the sum of the bumper rotation angle and potentiometer rotation angle . The relationships between and are In the case that , , and where , we obtain When it is assumed that is sufficiently small, , . After rearranging these relationships, we obtain where, We can calculate the bumper movement , which is in the direction of the collision, using
4.3. Accuracy of the Device
In this section, we describe a set of experiments conducted to confirm the accuracy of the collision-detecting device. We intentionally applied an external force to the bumper from the translational and rotational directions. We compared the true and calculated displacement of the bumper using (7) for three directions. Note that the maximum of movement range are 18.5 mm in the front-back direction, 20 mm in the horizontal direction, and 7.5 deg in the rotational direction. Figure 8 shows the movement of the bumper when an external force is applied to the bumper in the following cases: (i)motion in the front-back direction (−15 mm-15 mm at 3 mm intervals), (ii)motion in the horizontal direction (−15 mm-mm at 3 mm intervals), (iii)Turning (−5 deg-5 deg at 1 deg intervals).
The experimental results are shown in Figures 9–11. In these experiments, we applied an external force in particular direction. Ideally, the displacement in the other directions is zero. However, as the movement range increases, the displacement in other directions also increases. The desired directions, as shown in Figures 9(a), 10(b), and 11(c), exhibit satisfactory accuracy when the movement is small. The maximum errors are 2.5 mm in the front-back direction, 6.0 mm in the horizontal direction, and 2.5 deg in the rotational direction. The problem is that the link is passively-deformed when the movement is big. To reduce the error, we should change the link material from MC nylon to a metal.
In this study, we developed a prototype with the aim of realizing high mobility and safety. The developed wheelchair is an omnidirectional vehicle with a high level of ability when negotiating a step, gap, or slope. Collision detection is realized by installing a bumper around the vehicle. When the bumper collides with an obstacle, the obstacle does not come in contact with the main body of the vehicle. The collision-detecting device can calculate the collision direction from the measured displacement (position and orientation) of the bumper from the initial position. The collision-detecting device is composed of low-cost sensors. In future work, we will implement the collision detecting device in an electric wheelchair and add an intelligent function to the wheelchair such as an operation assistance system.
This paper was partially supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan, (MEXT) by Grant-in-Aid for Scientific Research (C) 21560265, 2009.
- B. E. Ilon, “Wheels for a course stable self propelling vehicle movable in any desired direction on the ground or some other base,” United States Patent 3, 876, 255, 1975.
- S. Ishida and H. Miyamoto, “Holonomic omnidirectional vehicle with ball wheel drive mechanism,” Transactions of the Japan Society of Mechanical Engineers C, vol. 78, no. 790, pp. 2162–2170, 2012.
- K. Yamada, T. Miyamoto, and S. Usui, “A study on a holonomic omnidirectional vehicle using 4 ball wheels,” Transactions of the Japan Society of Mechanical Engineers C, vol. 71, no. 708, pp. 2557–2562, 2005.
- K. Tadakuma, R. Tadakuma, and J. Berengeres, “Development of holonomic omnidirectional vehicle with “Omni-Ball”: spherical wheels,” in Proceeding of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '07), pp. 33–39, November 2007.
- M. Wada and H. H. Asada, “Design and control of a variable footprint mechanism for holonomic omnidirectional vehicles and its application to wheelchairs,” IEEE Transactions on Robotics and Automation, vol. 15, no. 6, pp. 978–989, 1999.
- N. I. Katevas, N. M. Sgours, S. G. Tzafestas et al., “The autonomous mobile robot SENARIO: a sensor-aided intelligent navigation system for powered wheelchairs,” IEEE Robotics and Automation Magazine, vol. 4, no. 4, pp. 60–69, 1997.
- H. A. Yanco, “Wheelesley: a robotic wheelchair system: indoor navigation and user interface,” in Assistive Technology and Artificial Intelligence, vol. 1458 of Lecture Notes in Artificial Intelligence, pp. 256–268, 1998.
- Y. Matsumoto, T. Ino, and T. Ogasawara, “Development of intelligent wheelchair system with face and gaze based interface,” in Proceeding of the 10th IEEE International Workshop on Robot and Human Communication, pp. 262–267, September 2001.
- Y. Kuno, N. Shimada, and Y. Shirai, “Look where you're going,” IEEE Robotics and Automation Magazine, vol. 10, no. 1, pp. 26–34, 2003.
- D. P. Miller and M. G. Slack, “Design and testing of a low-cost robotic wheelchair prototype,” Autonomous Robots, vol. 2, no. 1, pp. 77–88, 1995.
- U. Borgolte, H. Hoyer, C. Bühler, H. Heck, and R. Hoelper, “Architectural concepts of a semi-autonomous wheelchair,” Journal of Intelligent and Robotic Systems, vol. 22, no. 3-4, pp. 233–253, 1998.
- J. D. Yoder, E. T. Baumgartner, and S. B. Skaar, “Initial results in the development of a guidance system for a powered wheelchair,” IEEE Transactions on Rehabilitation Engineering, vol. 4, no. 3, pp. 143–151, 1996.
- R. Simpson, E. LoPresti, S. Hayashi, I. Nourbakhsh, and D. Miller, “The smart wheelchair component system,” Journal of Rehabilitation Research and Development, vol. 41, no. 3, pp. 429–442, 2004.
- R. C. Simpson, “Smart wheelchairs: a literature review,” Journal of Rehabilitation Research and Development, vol. 42, no. 4, pp. 423–435, 2005.
- A. Lankenau and T. Röfer, “A versatile and safe mobility assistant,” IEEE Robotics and Automation Magazine, vol. 8, no. 1, pp. 29–37, 2001.
- J. Protho, D. Poirot, and D. M. Brienza, “An evaluation of an obstacle avoidance force feedback joystick,” in Proceedings of the 23th Annual RESNA Conference, 2000.
- Y. Yagi, S. Kawato, and S. Tsuji, “Real-time omnidirectional image sensor (COPIS) for vision-guided navigation,” IEEE Transactions on Robotics and Automation, vol. 10, no. 1, pp. 11–22, 1994.
- C. Mandel, K. Huebner, and T. Vierhuff, “Towards an autonomous wheelchair: cognitive aspects in service robotics,” in Proceedings of the Towards Autonomous Robotics Systems (TAROS '05), pp. 165–172, 2005.
- J. Kurata, K. T. V. Grattan, and H. Uchiyama, “Navigation system for a mobile robot with a visual sensor using a fish-eye lens,” Review of Scientific Instruments, vol. 69, no. 1-2, pp. 585–590, 1998.
- Y. Satoh and K. Sakaue, “An omnidirectional stereo vision-based smart wheelchair,” Eurasip Journal on Image and Video Processing, vol. 2007, Article ID 87646, 11 pages, 2007.