Hideo Mori

A Robotic Travel Aid for the Blind

We have been developing Robotic Travel Aid(RoTA) “HARUNOBU” to guide the visually impaired in the sidewalk or campus. RoTA is a motor wheel chair equipped with vision system, sonar, differential GPS system, dead reckoning system and a portable GIS. We estimate the performance of RoTA in two viewpoints, the viewpoint of guidance and the viewpoint of safety. RoTA is superior to the guide dog in the navigation function, and is inferior to the guide dog in the mobility. It can show the route from the current location to the destination but can not walk up and down stairs. RoTA is superior to the portable navigation system in the orientation, obstacle avoidance and physical support to keep balance of walking, but is inferior in portability.

Development of the robotic travel aid “HITOMI”

Abstract The Robotic Travel Aid (RoTA) is a motorized wheelchair equipped with vision, sonar, and tactile sensors, in addition to a map database system. The visually impaired can get orientation, mobility and obstacle information from RoTA, and can inquire about their present location, landmarks and the future part of the route. The concept is implemented on a RoTA called “HITOMI”. It can guide the impaired to avoid vehicles along a road with lane marks or along a sidewalk marked with Braille.

The ultrasonic range finder for outdoor mobile robots

Ultrasonic rangefinders have already been used successfully for indoor mobile robots. However, in an outdoor environment, the sensor should be robust against noise from vehicle engines and other sound sources. The robust sensor has already been proposed, but it requires a high-performance processor. In this paper the authors propose a new ultrasonic ranging sensor which is simple and low-cost. This sonar is robust in noisy environments. A RTZ (return to zero) signal having a certain time duration modulated with a 40 KHz carrier is transmitted from a transducer, then cross-correlation is calculated between the transmitted wave form and the demodulated received wave form. If objects are present the calculated cross-correlation has relatively large value. The authors can measure the range from the sensor to the objects by the time interval between the starting time of the transmitted signal and the time which has the peak value. The experimental results show the robustness of this sensor against the impulse noises. Furthermore, the authors propose that several sonar sensors can work at the same time without mutual interference, when the different time duration signals are used as the transmitting signals.

Finding pedestrians by estimating temporal-frequency and spatial-period of the moving objects

A new method of finding pedestrians in a time sequence of visual images has been proposed, and its great practical applicability has been demonstrated. Walkers exhibit periodic motion in a quite different way from other moving objects. This periodicity, or in other words rhyth of walking, is the result of the walking action and can be observed in two kinds of periodic intensity change of the pedestrians image. So, pedestrians can be found if we look for these periodicities which are quite unique to them. To realize this idea, we estimate the temporal-frequency and the spatial-period of the moving objects. The temporal-frequency is the oscillation of intensity against time. The spatial-period represents the fluctuation of intensity along the trajectory of the object, and is referred to as the stride of walking. A pedestrian detection method using these two oscillations has the following advantages. (1) This method is independent of the absolute intensity or contrast of the objects. (2) Clothes, hairstyle, shape of body, illumination and the distance from the camera do not affect the reliability of detection. Finally, the algorithm is simple enough for real time operation. The detailed algorithm is presented here and its validity and practical applicability are examined in an experiment on asphalt paved road.

Color impression factor: an image understanding method for outdoor mobile robots

The color vision in the outdoor environment has two problems. The first is the hue shift of the object under the changes of the season, weather, the hour and the view position. The second is the hue shift of the object between in the sunny place and in the shaded place. We propose the color impression factor to memory the hue of the object. The color impression factor is defined as R-B. It is the function of the sunlight condition (sunny/shaded) and the hour. We show this factor is useful to discriminate objects from the shadows in the asphalt paved road-yellow tactile blocks from the asphalt paved road.

Danger estimation of the Robotic Travel Aid (RoTA) at intersection

We have been developing Robotic Travel Aid (RoTA) system since 1991 which guides the blind on a road or a sidewalk. One of the most difficult problems for RoTA is how to cross the intersection without a traffic accident. So, danger estimation for vehicles at the intersection is proposed in this paper. This method is implemented on an image processing system. The location, velocity, and the moving direction of a vehicle are measured by computer vision and its danger coefficient is evaluated. About 90% of vehicles in a T-shaped intersection have been correctly interpreted in danger judgments in real world scenes.

A method of pedestrian detection based on rhythm of walking

It is important for mobile robots and security purposes to discriminate a pedestrian among moving objects in a video. This paper proposes a method which discriminates a pedestrian from other objects by using periodic motions of the feet, and the characteristics of the rhythm of pace and stride. This method uses brightness changes in sequential images of a moving object contacting with the ground, and extracts the main component of the frequency using a power spectrum estimation. Therefore, the method is independent of pedestrians appearance such as clothes, build, and hair style. The system realizing this method consists of three processes: moving object detection which uses the difference between successive image frames; tracking of the moving object using a moving model with an extended Kahman filter and an observation model; and detection of the pedestrian based on rhythm of walking using the difference of brightness between images on successive frames. The whole process is performed in real time. Experiments using real scenes confirm the effectiveness of the proposed method: 446 pedestrians out of 470 were successfully detected (detection rate 94.9%), and 101 persons out of 106 were successfully detected as non-pedestrians (96.2%).

Sensory selection in vehicle detection and avoidance

Abstract A general paradigm for vehicle detection and avoidance by proper selection of visual and sonar sensors is presented. The most appropriate sensor for detection and navigation of the robot is selected in accordance with the sensor functions and limitations. This strategy is activated when one sensor cannot obtain enough information for navigation of the robot because of sensor limitations. Five types of actions based on stereotyped motion are used for the navigation system: Moving Along Wall, Moving Along, Moving Toward, Tracking Motion and Danger Estimation. The first is sonar based and the rest are vision based actions. Visual detection of the vehicle is based on the locomotion strategy “Sign Pattern based Stereotyped Motion”. The sign pattern of the vehicle is the shadow underneath the vehicle, which is darker than any other parts of the paved road. The robot detects the sign pattern of a vehicle from a distance of more than 30 m and extracts its front or rear shape on 2-D image by video rate processing. Moreover, to make a decision for further action of the robot, a time series information of vehicles on the paved road are provided during tracking process.

The Robotic Travel Aid “HITOMI”

Publisher Summary Various kinds of electronic travel aid (ETA) have been developed for the visually impaired. Among them, the moat sensor and sonic guide have been available for 20 years, but have not yet become widespread. Recently, vision-guided vehicles have been investigated by many researchers. The robotic travel aid (RoTA) is not a replacement for the guide dog, but it is an advancement of ETA. RoTA is a motorized wheelchair equipped with vision, sonar, and tactile sensors, in addition to a map database system. The visually impaired can get orientation, mobility, and obstacle information from RoTA, and can inquire about their present location, landmarks, and the future part of the route. The concept is implemented on a RoTA called “HITOMI.” It can guide the impaired to avoid vehicles along a road with lane marks or along a sidewalk marked with Braille.

A locomotion performance learning of the mobile robot

Improvement of the environmental model to avoid the lapse time of observation and action by analyzing the data of the last run is called locomotion performance learning. The algorithm of the learning is expressed by rewriting rules on the trajectory data. The algorithm is implemented on mobile robot HARUNOBU-4, and tested in the university campus. Experimental results show that after the learning 83% of the observation times and 18% of locomotion times are cleared.