We have developed a new type of 3D LIDAR, which is small, light weight and low cost. The size and weight are important factors of the aimed sensor to use with wide range of robot vehicles, helicopters and airplane, and small vehicles. To achieve compact size and light weight construction the sensor has single pair of laser transmitter and receiver, and scanning motor on which a vibrating mirror is placed. The mirror is driven by the resonant frequency current supplied through contactless power supply unit. Experimental results of the prototype shows that the sensor of comparable size and weight with recent 2D sensors can obtain 3D range data of 8000 points in 20 Hz with 270 degree horizontal and 40 degree vertical views both in indoor and outdoor.

When an active volcano erupts, a restricted area is typically set according to the eruption level. However, it is very important to observe eruption products inside of this area to predict the timing and scale of volcanic hazards, such as debris flows. Therefore, we propose a robotic observation system for active volcanoes that is composed of a multi-rotor unmanned aerial vehicle (UAV) and a mobile ground robot. To deliver the ground robot safely from the multi-rotor UAV to the ground, we implemented a sky-crane mechanism and confirmed the feasibility of the mechanism theoretically. In this paper, we introduce our volcano observation scenario as well as the observation system and sky-crane mechanism we have developed. Finally, we report on a field test conducted at Mount Asama in September 2013.

This paper presents tracking algorithms of a mobile robot that tracks a human in front. The mobile robot, which is a differential-driven wheel type, is equipped with a laser range finder to perform human tracking in front. Initially, we recommend the torso part for the robust tracking of the human body in outdoor environment by a laser range finder. To track a human in front, we define a virtual target determined by the velocity of the target human. For a more efficient movement of the mobile robot, a desired heading direction of the robot considering motion vectors of the robot and the human is proposed.

For the construction of the mobile robot system, it is necessary to determine a lot of parameters like the feedback gain and the clip parameters of artificial saturation. And it is difficult to decide suitable parameters by analytical technique because of its non-linearity and complexity. In this paper, we propose the method of the mobile robot control system parameter design by a numerical simulation and heuristic optimization using the enough computer power. We describe the model of the system as iterative numerical calculation instead of analytical time function. This model can suit the real control system, and it is straightforward to be built. And we show the experimental results of the automatically decided feedback gains by using proposed method for the linear feedback trajectory tracking controller of the small-sized autonomous mobile robot system, which runs in relatively high speed up to 5 meters per second as an example.

This paper presents tracking algorithms of a mobile robot that follows a human body moving at high speed in unstructured outdoor environment. The mobile robot, which is a differential-driven wheel type, is equipped with one laser range finder to perform high-speed human tracking and obstacle avoidance. Initially, the waist part of the human body is found the best part of the human body for robust tracking by a laser range finder. Next an obstacle avoidance algorithm considering the relative velocity between the robot and obstacles is proposed. It is shown that the proposed human tracking algorithms based on the Kalman filter performs well even in the case of the target occlusions and temporary losses. These tracking algorithms have been applied to a marathoner following robot that carries the marathoner's personal belongings in many different outdoor environments.

In this paper, we present the current progress of our approach to identify and follow a target person for a service robot application. The robot is equipped with LRF and Omni directional camera. Our approach is based on multi-sensor fusion in which a person is identified using the panoramic image and tracked using the LRF. The selection of the target person is implemented to improve the identification when multiple candidates are detected. Our approach is successfully implemented on a mobile robot. A simplified target person following behavior is implemented to focus on the proposed method's efficiency. Several experiments are conducted and showed the effectiveness of our approach to identify and follow human in indoor environments.

We are trying to develop an easy autonomous map making method for indoor mobile robots, using the property of the usual buildings, which we can assume that the major walls are arranged parallel or perpendicular. Based on these properties, the robot can find its own direction easily, with its surroundings range data, so that the accumulated error in the calculated direction can be avoided. In this paper, we propose a method to know the robot direction using scanned range data of the environment walls, and the method to build the map by connecting the scanned range data using this property. We also present an example of experimental results of indoor map making by a mobile robot without using the odometry, which shows the effectiveness of the proposed method.

Effective detection of people is a basic requirement for robot coexistence in human environments. In our previous work [1] we proposed a method for people detection and position estimation using multiple layers of Laser Range Finders (LRF) in a mobile robot. We extend our work by introducing laser reflection intensity as a novel feature for people detection, achieving significant improvement of detection rates. In concrete, we propose a method for calibration of laser intensity data, a method for segment separation using laser intensity, and introduce two new intensity-based features for people detection: the variance of laser intensity and the variance of intensity differences. We present experimental results that confirm the effectiveness of our multi-layered detection method including laser intensity.

Successful detection of people is a basic requirement for a robot to achieve symbiosis in people's daily life. Specifically, a mobile robot designed to follow people needs to keep track of people's position through time, for it defines the robot's position and trajectory.

We are developing robots for inspection of the under floor of houses. The developed robot system is reported in this paper. The mobile robot platform is based on a crawer type robot developed for rescue purposes. As sensors, a pan-tilt-zoom camera, top-view camera and SOKUIKI sensor are used. We constructed a test field and verified the performance of the robot.

In this paper, we propose a novel human detecting system using several stationary and moving laser range finders (LRF). The occluded area where the stationary sensors cannot measure will be covered by the actively moving sensor. The occlusion is perceived by overlaying visible area of the stationary sensors. The moving sensor will move to the target position where the sensor can measure the occluded area. Finally, the measured information of all sensors will be merged for data fusion. The experimental results show the effectiveness of the system.

This paper presents an approach for vehicle 3D localization in outdoor woodland environments using a loosely coupled multisensor system. The vehicle 3D dead reckoning is computed using a wheel encoder and an IMU. Dead reckoning is corrected from three different sources: a) using a tilted lidar for road detection and computation of the vehicle position within the road which is then corrected towards a 2D road centerline map given in advance. b) DGPS 2D or 3D data as available. c) Under tree foliage DGPS blackouts commonly occur, specially when measuring height, therefore the use of a barometer for correcting height is proposed. An extended Kalman filter is used for sensor fusion and pose estimation. Finally, the estimated vehicle height is added to the 2D map obtaining a 3D road centerline map with width (measured by the tilted lidar). Thoroughly experimentation on real mountainous woodland paths show the usefulness and robustness of the proposed approach.

In this paper, we propose a solution for human identification and localization with a mobile robot problem that implements multi-sensor data fusion techniques. This solution is designed for an autonomous luggage cart. The system utilizes a new approach based on identifying the target human visually from an omni directional camera then localizing and tracking him using LRF. This approach is composed of "registration stage" and "identification and localization stage". The registration stage extracts all necessary information needed including patches from the clothes. The identification is made using a modified pattern-matching algorithm to fit to a real time application. The tracking is implemented using a positions history structure to keep record of all positions of surrounding objects and the identified human.We implemented the proposed approach in fixed configuration to test its effectiveness.

This work deals with navigation of an omni-directional mobile robot with active caster wheels. Initially, the posture of the omni-directional mobile robot is calculated by using the odometry information. Next, the position accuracy of the mobile robot is measured through comparison of the odometry information and the external sensor measurement. Finally, for successful navigation of the mobile robot, a motion planning algorithm that employs kinematic redundancy resolution method is proposed. Through experiments for multiple obstacles and multiple moving obstacles, the feasibility of the proposed navigation algorithm was verified.

This paper explains the design and implementation of a discreet landmark capable of modifying its properties in order to be able to differentiate itself from its surrounding environment. In this case, differently from common devices, our landmark does not make use of neither light, wave reflection, or radio frequencies, but it makes use of temperature properties of a peltier device which is able to increase or decrease its temperature. By having different characteristics from its surroundings, in this case a temperature landmark can be robustly found and tracked in complex indoor environments using thermo infrared cameras. The proposed system composition and configuration, landmark finding, extraction and tracking methods are also explained and effectiveness of this system is described and evaluated.

This paper describes a grasp planning for a mobile manipulator which works in real environment. Mobile robot studies up to now that manipulate an object in real world practically use ID tag on an object or an object model which is given to the robot in advance. The authors aim to develop a mobile manipulator that can acquire an object model through video images and can manipulate the object. In this approach, the robot can manipulate an unknown object autonomously. A grasp planning proposed in this paper can find a stable grasp pose from the automatically generated model which contains redundant data and the shape error of the object. Experiments show the effectiveness of the proposed method

The purpose of this research is to develop a robot system which helps humans to remotely accomplish a daily given task such as shopping. This teleoperated system is based on simple mutual human-robot cooperation where the person remotely communicates with the mobile robot. We define the specific task of buying FRESH foods in a supermarket from a remote location. In order to do shopping operations, the robot has to be able of grasping a large amount of objects with different textures, shapes and weights which include fruits and vegetables with soft and irregular forms. After the user chooses the product to buy, the process is the next, firstly the robot has to find the object, then grasp it and then place it into a shopping basket. In this work, we built a system according to the previously explained requirements which involves autonomous navigation, environment perception, object manipulation and teleoperation. In this paper, we present the developed suction hand for picking fresh foods and evaluate its operating performance through experimental results

This paper describes motion planning for a mobile manipulator which works in real environment. Mobile manipulators that can manipulate an object was developed up to now. We assume that object grasping is not restricted to just one grasp way and robot can move freely as far as it is in its operational area of the object. This paper proposes the motion planning for object grasping under the previous explained conditions. There are two major issues to detect the robot pose. The first problem is pose error of the robot hand. The second problem is kinematical redundancy of the mobile manipulator. The pose is evaluated from the amount of joint motions for recovery of hand pose error. Experiments show the effectiveness of the proposed method.

We have developed a 2D laser range sensor suitable for mobile robot platforms. The sensor features compactness, lightweight, high precision and low power consumption, and provides the wide scan angle with high resolution, which is very important for environment recognition by mobile robots. The basic technology for measuring the distance between the sensor and objects are; using amplitude modulation of light waves and detecting the phase difference between transmitted and the received one. This paper explains the specification of the proto-type sensor, the method of distance measurement and examples of experimental results.

Despite that omni-directional mobile robots have been investigated and used popularly, there are rarely useful command systems and control methods for practical applications. In this research, a command system to describe the navigation task for an omni-directional mobile robot is developed, and a motion generation method considering the robot geometry and the given trajectory is proposed. Furthermore, a control method to track the given linear and circular trajectories is proposed. A closed form kinematic model was utilized for motion generation and control as well. A redundantly actuated omni-directional mobile robot that consists of three caster-type wheel mechanisms with high performance embedded controller module was developed for the experiments. And some experiments in the real environment were carried out to verify the effectiveness of the proposed command system and the performance of the motion generation and the trajectory control method.

We are interested in the dynamical mobility of a simple mechanism with two links and one-motor, which moves in one dimension. It can move with rotation of the lower link led by the swing of the upper link. We have developed a two-link-one-motor experimental robot, implemented a detailed simulation for this system which include backlash or shock in landing, and designed a non-linear feedback controller to realize one step stable motion of this mechanism.

The final objective of the authors is to realize mobile robot navigation in walkway of outdoor environment. The path along the walkway which is measured correctly together with landmarks must be given in the framework in this paper. The robot identifies its position by means of odometry, DGPS and laser range finder (LRF) during the motion along the path. This work contributes to the map building of landmarks along the walkway. To make the map, RTK-GPS, odometry and LRF are used for the sensory devices and Kalman smoothing technique is also incorporated to interpolate trajectory of the scanning LRF equipment between the two point that RTK-GPS measurement took place. The scanning by LRF is performed to acquire the 3-D shape of objects along the walkway. The trajectory presumed properly and well organized shapes of the objects are reconstructed.

This paper describes 3-D shape modeling performed by a mobile robot. We propose a method in which the robot in the real environment acquires the accurate shape and constructs a 3-D model of an object using Computer Vision techniques under the condition that position and shape of the object is unknown. 3-D modeling is performed from image streams which are captured by a camera placed on the robot. The results show the effectiveness of our method.

It is important and necessary to develop a teleoperated mobile robot to have reconnaissance operation inside of the extreme earthquake stricken building or underground town. The present authors aim at developing such a teleoperated mobile robot. In this paper, a prototype of the teleoperation and man-robot interface system is proposed. The tele-operated robot and the remote operation station is linked with wireless network and the operator can command the robot. One feature point of this system is to provide a live omni-directional panoramic view image and live map to the operator on the display of the remote operation station. The live map represents the floor plan of the moving environment and it is provided by SLAM technology with LRF scan data. It proves very effective to have combined use of the panoramic image and the live map. Experimental set up and integrated experiments are also reported in this paper.

This paper describes how to acquire 3-D shape of an object and to estimate robot pose by observing an unknown object. A single camera is placed on the robot, image streams of the target object are captured by the camera on a mobile robot moving around the object. Computer vision techniques are utilized under the condition that shape, size and accurate position information of the target object is not given in advance, but the robot finds the target object and reconstructs the 3-D object shape by itself. In addition, it is necessary that the robot grasps relative pose between itself and the target object. Experimental result show the effectiveness of our method in point of robustness and accuracy for the mobile robot.

The authors aim at map based outdoor navigation of a mobile robot. In navigation, robot position is fundamentally obtained by odometry. However, the position is misaligned as the robot moves because odometry has cumulative error. DGPS measurement data may cancel its position error. The framework of EKF is used for the modification and the fusion between odometry and DGPS measurement data. The DGPS measurement data, however, could have large error because of multipath near buildings. In this paper, the authors propose a method which eliminates erroneous DGPS measurement data when odometry robot position is fused, and confirm the validity of this approach.

This paper describes a sequence of methods for controlling the vehicle with unknown operating properties, such as an air cushion vehicle, a submarine and an airship. We took up Air Cushion Vehicle (ACV) as an example of such a vehicle, and studied its motion planning based on acquired data. ACV in this paper has three simple unit motions (left-turn, right-turn and an advance), and can execute one of the unit motions optionally. After the execution, ACV measures its own position by itself and acquires data of how it moved in the real environment. Then it plans the motion that arrives at a target position using the acquired data. In this paper, we propose a sequence of these approaches and show the effectiveness of them by experiments.

This paper describes a system which uses a mobile manipulator as a teleoperated tool for accessing and manipulating remote objects, in our challenge to extend mobile robot potentials and usage in human daily life. The specific task we set up in this research is to help humans browse books located in a library from a remote location via the Internet. This task was decomposed into three major parts which are, the extraction and return of a book from a bookshelf, its browsing, and the teleoperational interface needed for humans to access to this system via a media such as the Internet. We built and realized a robot system which enables remote humans to access and browse books in a library from the Internet.

This paper presents a method of building a structured map, which consists of objects such as furniture. We represent a map as a graph, in which a node represents an object and an arc represents a relative pose between objects. The robot localizes itself and builds a map using odometry readings and sensor data obtained by object recognition. To correct the map distortion caused by errors in the data, the robot utilizes loops as geometric constraints, and imports geometric knowledge provided by a hand-made map. Experiments show that the root successfully built a map of corridors, and a map of a room having many objects.

This paper presents a novel design of indoor airship having a passive wheeled mechanism and its stationary position control. This wheeled blimp can work both on the ground using wheeled vehicle part and in the air using the floating capability of the blimp part. The wheeled blimp stands on the floor keeping its balance using a caster-like passive wheel mechanism. In tele-guidance application, stationary position control is required to make the wheeled blimp naturally communicate with people in standing phase since the stationary blimp system responds sensitively to air flow even in indoor environments. To control the desired stationary position, a computed torque control method is adopted. By performing a controller design through dynamic analysis, the control characteristics of the wheeled blimp system have been found and finally the stable control system has been successfully developed. The effectiveness of the controller is verified by experiment for the real wheeled blimp system.

Our purpose is the realization of a system able to access objects located at remote places, by integrating Internet technologies and robotic engineering developments such as mobile robots. As an example, in this research, we are developing a system for browsing books from remote places through the Internet with a robot. In order to do browsing operations, the robot has to recognize the alignment state of a bookshelf itself and to pick up a book correctly. This paper also describes the developed sensor for recognizing the posture of a book and the plan for extractional operation in the environment of a general library. In addition, we conducted experiments by the developed system, and summarize the consideration about this system.

Proposes an indoor navigation system for an autonomous mobile robot including the teaching of its environment. The self-localization of the vehicle is done by detecting the pose of corridor fluorescent tubes with a camera pointing to the ceiling. A map of the lights based on odometry and used later for navigation tasks is first built by remotely controlling the robot. The map distortion due to positioning errors is corrected to facilitate route definition by detecting and closing open cycles extremities. Paths defined on the modified map whose geometry differs from the robot one are then converted automatically into the robot map so that the robot can refer to it and cancel odometry errors during navigation.

We have proposed a navigation method for mobile robots in indoor environments based on a memorized sequence of images and robot's motion. The method consists of two stages: route teaching and playback navigation. At the teaching stage, the robot is controlled to move along a designated route in an environment, records robot's motion, and memorizes environmental images. In the course of autonomous navigation, the robot plays back the recorded data. It compares the currently taken image with the memorized one so that it estimates its position, and then calculates a trajectory to track the memorized route in real-time. We use an omni-directional camera to perceive environmental information, and extract the vertical edges existing in environment as landmarks in this method. In this paper, we report on the use of the color on both sides of vertical edges so as to match these edges more robustly, and explain the autonomous navigation in backward direction using the forward taught data.

This paper describes a system which uses a mobile robot as a teleoperated tool for accessing and manipulating remote objects. The purpose of this study is to develop a robot system which helps humans to accomplish remotely a given task in their daily life, based on simple communication and mutual cooperation between them and a teleoperated mobile robot. The specific task we set up in this research is to help humans browse books of a library from a remote location. In this work, we build such a system accordingly to its basic requirements involving autonomous navigation, environment perception, book manipulation and teleoperation. In this paper, we present the developed book browsing robot system, its teleoperation human interface and evaluate its performance and operating efficiency through experimental results.

This paper presents a navigation system based on an inaccurate map. The map we consider here is a hybrid of a topological map and a geometrical map so that it can be built easily and permits changes in object locations. A localization scheme and an object recognition technique are introduced in order to keep the robot pose consistent on such an inaccurate map. To cope with the problem that a path may also be inaccurate on an inaccurate map, the robot corrects the path based on its pose estimated by the localization method while tracking the path. An experiment shows that the robot successfully navigated in an indoor environment, recognizing several kinds of objects.

This paper presents a vision based autonomous navigation system for mobile robots in an indoor environment by teaching and playing-back scheme. The system uses an omnidirectional image sensor to perceive the environment, and extracts vertical edges as feature lines. The system memorizes a sequence of environmental images and robot's poses during teaching stage. In the course of playback navigation, the system calculates the robot's position difference from the memorized and currently taken images, and then decides the trajectory to track the taught route. The detail algorithm and the effectiveness of this method with experiments are shown.

We report our remote viewing system using mobile robotic avatars via Internet with a Web browser. Mobile robots serve their sensing and action as avatars for remote viewers, who are ordinary persons on the WWW. This system is a tool to obtain the human behavior in an art museum for the KANSEI special project. Through many trials of single robot/user version at the Tsukuba art museum, we discuss open problems on it. Then, we propose basic idea using multiple robotic avatars to solve these problems and extend our system.

This paper describes a strategy of a mobile robot walkway following using color image. There are different colors in a walkway and lawn area alongside the walkway. The walkway area is extracted by an image processing. Color difference among walkway and waysides is considered in the image processing. Robustness against daylight change for segmentation of walkway area is also considered. The robot moves to the direction toward vanishing point of the walkway which is obtained from the image processing. Repeating these processes, the walkway following can be accomplished.

Proposes a method of global localization on a map with large uncertainty. Since the pose of a mobile robot represented in a global frame of reference might be inconsistent on an inaccurate map, the method represents the robot pose in a local frame attached to a landmark. When the robot finds a new landmark, the robot transforms its pose from the old landmark frame to the new one based on the relative pose between the landmarks. Map errors are represented by probability density functions defined on these relative poses. The paper presents an extension of Markov localization which is augmented so as to incorporate the map errors into data fusion process, and shows experimental results.

A quantitative evaluation method of manipulative difficulty for a tractor pushing or towing multiple trailers is introduced. A manipulative difficulty index (MDI) thinking about imperfect measurement is proposed. This difficulty varies if physical parameters such as the position of the joint or the number of the trailers is changed. The authors focus on this change when some state variables have measurement errors. Also, quantitative comparisons for typical examples of the change of physical parameters of tractor-trailers under the above case are presented.

Navigation in unknown environments requires the robot to obtain the destination positions without a map. The utilization of model-based object recognition would be a solution, where the robot can estimate the destination positions from geometric relationships between the recognized objects and the robot. This paper presents a robot system for this kind of navigation, in which the robot navigates itself to the room designated by room number. The robot has an environment model including a corridor and a door with a room number plate, and utilizes the model for the efficient recognition of the objects and the estimation of their positions.

This paper propose a new method of sensor fusion of an omni-directional ultrasonic sensor and an omnidirectional vision sensor. A new omni-directional sonar, which we developed, can measure accurate distance and direction of reflecting points, and an omnidirectional vision can give direction to edges of segment. We propose a sensor fusion method using both the reflecting points measured by the sonar and the edges of segment measured by the vision, based on the angles. Those data are different in character, so they compensate each other in the proposed method, and it becomes possible to get better information which are useful for environment recognition of mobile robots. We describe the proposed method and an experimental result to show its potential.

We report our remote appreciation system using a mobile robot driven by remote control via the Internet using a Web browser. The robot in the museum is an avatar that acts for people who, for various reasons, cannot visit the museum in person and would like to visit the museum from distant homes or offices. This work is part of the special project on "modeling the evaluation structure of KANSEI" at the University of Tsukuba. We also discuss problem on the infrastructure of global network for our system and its solution in "giga-bit/high-speed network".

This paper describes a strategy of a mobile robot walkway following using color image. There are different colors in a walkway and lawn area along side the walkway. The walkway area is extracted by an image processing using the difference of color. The robot moves to the direction of vanishing point which is obtained from the image processing. Repeating these processes, the walkway following will be accomplished.

A geometric map which quantitatively represents the locations of entities in the environment are widely employed for indoor navigation. Navigation based on a geometric map provides high accuracy in positioning, but making an accurate map for a large area is difficult. To cope with this problem, this paper proposes a framework of indoor navigation based on a partially quantitative map. The map comprises the models of geometric entities in the environment, the locations of which are partially defined. Using the partial information, the robot searches and recognizes entities as a landmark while navigating in the environment.

This research work contributes to an active vision system for an gas pipe inspection robot moving inside of the pipe. The robot must be able to know what shape of the pipes where the robot is moving. The shapes of the pipe include straight, L or T. Also, when it is moving in the straight section, the robot must detect the relative angle with respect to its principal axis. The authors propose to use a laser spot array and TV camera for the vision sensor, which can find the three dimensional position of each spot on the surface of the pipe by means of triangulation. The shape of the pipe inside can be reconstructed by the information of the camera. A method is also presented to distinguish the shape whether it is straight or not.

Proposes a method of adding the amplitude of ultrasound echo from reflecting points. An omni-directional sonar which we developed, can measure accurate distance and direction of the reflecting points, and it is possible to measure amplitude of the echo which corresponds to the reflecting points. We propose a method to add information from the amplitude of the echo from the reflecting points for environment recognition. This method can give useful information such as character of reflecting objects and it makes possible to correspond each reflecting point with others using this information. We describe the proposed method and an experimental result to show its usefulness.

A mobile robot can use the walls or the pillars to localize itself when it navigates in indoor environment. However, in open space or outdoor environment there are few easy detectable and stable objects that the robot can use. In this paper, we propose a method for the detection of braille blocks, which are originally used for visually handicapped people, for autonomous mobile robot navigation. To recognize the braille block, a CCD camera and a laser fan beam projector are used as sensor to detect bumps on road surface. This paper also presents the experimental results of braille block following using the sensor system to detect the braille block position and orientation. This experiment shows effectiveness of the sensor system for the braille block recognition and implies the possibility of braille block based mobile robot navigation.

This research aims at development of sensors for small size indoor mobile robots. We have proposed a new sonar-ring which can measure accurate direction and distance to reflecting points rapidly for this purpose. This new sonar-ring needs to receive echo signal by multiple receivers and to detect multiple Time-of-Flights (TOFs) in received signal at each receiver simultaneously for achieving fast and accurate measurement. However, it is impossible to satisfy them by conventional circuit. This paper proposes 30 channel 1 bit wave memory system to achieve these two points simultaneously and shows its usefulness.

The index of the manipulative difficulty for a mobile robot towing and pushing multiple trailers to follow a straight line is proposed. It will be useful to design such a tractor-trailers system. Some examples of the manipulative difficulty index was calculated by changing the number of trailers when the mobile robot pushes and tows the trailers.

A sonar-ring is one of the most popular sensors for indoor mobile robots, because it is simple and gives omni-directional distance information directly. However, it is difficult to measure the accurate direction of reflecting points by a conventional sonar-ring sensor. Further more, conventional sonar-ring sensors are slow to get full 360 degrees information due to sequential driving of transducers for avoiding interference. We propose a new sonar-ring sensor system for a mobile robot which can measure the accurate bearing angles of reflecting objects in a single measurement. The proposed system employs measurement by using differences of time-of-flight and by simultaneous transmit/receive of all directions, and consequently achieve fast measurement. We implemented a prototype of the proposed sonar-ring on a mobile robot. Experimental data show the effectiveness of the proposed system.

We developed APCS (autonomous position correction system) that can autonomously cancel the error of the estimated robot position from odometry by detecting flat walls using ultrasonic sensing. When it detects flat walls in the environment, this system corrects the estimated position using maximum likelihood estimation (MLE). The feature of this system is that it can correct the position not being concerned with the behavior of the robot because the system autonomously decides the trigger of the position correction. We show the algorithm and implementation of APCS, and some experimental results to confirm feasibility of the system in a disordered environment.

Conventional wall following with an ultrasonic sensor uses only range data to the nearest reflecting point. However, the bearing angle information to the wall is more useful for a wall following motion. In this paper, we propose a simple wall following algorithm, where the robot moves perpendicular to the direction to the nearest reflecting point. Also, in conventional ultrasonic pulse-echo sensing, an accurate target bearing measurement is often regarded as difficult due to the wide directivity of ultrasonic transducers. However, by assuming that the ultrasonic echo returns from a single direction, the bearing angle can be measured. A new sensing method is also proposed to determine accurately the bearing angle to the reflecting point by a single ultrasonic transducer. This paper also presents experimental results from mobile robot wall following experiments using only bearing information measured by a single ultrasonic transducer. These experiments illustrate the effectiveness of proposed method.

This paper proposes a new method of position correction for a mobile robot on rough terrain. The strong point of our method is that no external sensor is needed for position correction. The information about position correction is derived from comparing between the estimated position and elevation map of the terrain by using the knowledge that the robot must touch the ground. Some experimental results are also shown.

The purpose of our research is a realization of the autonomy to deal with the real environment of mobile robots. In this paper, the concept of the autonomy in the robot is discussed first, the "long term activity" as a benchmark problem for the autonomous mobile robot is proposed, and the elementary technologies to realize a autonomous robot with such an ability is considered. Our mobile robot Yamabico-Liv which is being constructed for the experiments of long time activity is also presented.

Start of the above-titled section of the conference proceedings record.

In this paper, we report the outdoor navigation of an autonomous and self-contained mobile robot using the perceived route map (PRM) generated through human assisted route teaching. The PRM includes the path from the start to the goal taught by the operator and landmark information are automatically generated by the robot itself. The target environment is a paved or tiled pedestrian walkway. The pedestrian walkway can be assumed to be a two dimensional plane along with a wall, a hedge or a tree, etc., which can be utilized as landmarks for estimating the robot position. The robot is assumed to have sensors to detect landmarks and obstacles. A walking person or bicycle is assumed to be a moving obstacle.

We propose a new mechanism of a unicycle. One feature of this robot is the shape of the wheel which is similar to a rugby ball. The other feature is that the body is separated into upper and lower parts. We give the details of a mechanism of the robot, simple controller system, and some results of a performance experiment using the designed controller. We present experimental results that show that the robot can move in a straight line and steer itself by the proposed mechanism.

This paper describes concept and realization of IRoN (Inter Robot Network), a wireless communication network to support cooperation among mobile robots. From the point of view of the user (application programmer), IRoN has the following features: a list of surrounding robots with current position and speed is always available (by so-called implicit communication). Additionally, communication with any robot can be initiated from the user program explicitly (by so-called explicit communication). The paper also describes a simple application example: how simultaneous motion of two mobile robots can be achieved. Three different user program examples using different features of IRoN are described. The achieved motion delay ranges from about 1000 ms in the first user program, down to 50 ms in the third user program. IRoN will be used for further cooperation experiments involving three robots; a first experiment is reported in the conclusion.

We are interested in the operation facilities of vehicle that are simple even for persons who are not experienced in vehicle operation. One idea simplifying the vehicle operation is to separate the operation from the mechanism of the vehicle. In this system, the human operator specifies a temporary goal position of the mobile robot by touching the monitor in which front view images are displayed. The robot then travels toward this goal position. The path to the goal position is generated by the system and shown on the front view images. Therefore, the operator need not practice how to operate steering wheel or accelerator. We have constructed an experimental setup and evaluated it by controlling the robot.

We propose a practical approach which allow a tractor-trailer robot to plan and navigate a path, considering its shape and its kinematics constraint, however, without generating the configuration space for the sized robot. The operator can choose his preference of forward or backward paths by motion cost assignments. The path is generated in three stages: 1) road map analysis, 2) robot's states and transitions states generation, and 3) path search and motions generations. The planner has been tested on a tractor-trailer robot using different trailer sizes, demonstrating its ability for automatic generation of path, which may include even backward motions.

A goal of this research is to successfully accomplish a long distance navigation task, including "passing through a doorway", by an autonomous robot equipped with a manipulator. In our approach to this problem, we apply the concept of action primitives to the mobile manipulator control system. Action primitives are defined as unit elements of a complex behavior, such as door opening behavior. Basically, the action primitives control a robot according sequences of planned motion primitives. But as an important feature, each action primitive is designed with an error adjustment mechanism to cope with accumulated positioning error of the mobile base. In this paper, we report the design and implementation of action primitives for door opening behavior for our experimental robot, and show experimental results of an autonomous mobile manipulator's "passing through a doorway" using sequences of designed action primitives.

We present research on long distance outdoor navigation based on the estimated position for a mobile robot. We discuss the generation of the route map given to the robot in advance of autonomous navigation. We propose how the robot generates the route map including landmarks while a human operator takes it to the goal once. By our proposed method, it will be easy to make a large size route map for long distance outdoor navigation.

The purpose of this study is to realize autonomous navigation of a mobile robot with reference pre-recorded images, without any environment maps. The strategy of navigation in this research is that the differences of position and orientation of robot between the reference one and the present one are continuously estimated from true images, and are used in the locomotion control commands. In this paper, we use only vertical lines in the image as extracted features, and propose the method to calculate the estimated differences of position and orientation from two images. We also show some results of simulations and experiments using an actual mobile robot, and examine its reliability.

Presents a robust method for an autonomous mobile robot with a sonar-ring to follow walls. The sonar-ring consists of multiple ultrasonic range sensors. The proposed wall-following algorithm makes a robot able to follow a wall in various shapes such as a square wall, a circular wall etc. The autonomous mobile robot "Yamabico" is used for experiments after being equipped with a 12 directional sonar-ring. The on-board controller of the robot decides its motion based on sonar-ring range data every 3 centimeters going forward. The authors carried out many experiments with this autonomous mobile robot, and investigated the validity and the limits of this method.

The usual method for position estimation of a wheeled mobile robot is odometry. However, it has the problem of gradual error accumulation when the robot moves. To solve this problem, we place several reflectors sparsely in the robot's work-space as landmarks, so that the robot can correct its estimated position when detecting the landmark. The new estimated position of the robot is calculated by the maximum likelihood estimation (MLE) by both the position information estimated by odometry and the reflector detecting sensor system (ReDS) using the laser beam. ReDS, which we developed, can detect the reflector at most 3 meters away from the robot in the indoor environment. Practical experiments show that the estimated position obtained by this system is precise enough to be useful.

We propose a position estimation technique for nonstop outdoor navigation of an autonomous mobile robot. The proposed position estimation technique is based on maximum likelihood estimation. To cope with the parallel processing of internal and external sensor information and time delay in the sensor data process, we introduce the retroactive positioning data fusion technique. The proposed technique is implemented on our small size autonomous mobile robot. An experimental result is shown, in which our robot could navigate itself without stopping even when it takes several seconds of processing time to detect landmark from external sensor data.

An aim of this research is to realize a behavior of opening a door and passing through a door-way using an autonomous mobile robot equipped with a manipulator. This behavior is realized by integrating several sub-tasks, such as, finding a door knob, pushing the door to open by cooperation between a manipulator and a locomotion. First, we pay attention to one important sub-task, pushing the door. To realize the sub-task, a mobile robot needs to cooperate with an equipped manipulator. In this paper, we propose how to implement the sub-task on the robot, and show experimental results of it.

Ultrasonic sensors are very useful for mobile robots because they have the advantage that the systems are simple and are easy to handle. When a mobile robot is navigated using an ultrasonic sensor, the map of the environment should include information about the reflection characteristics of objects. For this purpose, the map using a vector expression is better than a grid map. In this paper, an environment reconstruction method using a vector map is proposed. In this method, the environment is reconstructed from the data obtained by using our novel ultrasonic sensor which can measure the normal direction of walls, and the next sensing point is determined automatically. The experimental results of a map construction using this algorithm are shown. As a result of the experiments, it is found that the measurement of walls is possible using this method and the effectiveness of the planning algorithm for the sensing point is verified.>

Discusses the trajectory control for a wheeled inverse pendulum type mobile robot. The robot considered has two independent driving wheels on the same axle, and a gyro type sensor for measuring the inclination angular velocity of the body and rotary encoders to measure the wheels' rotation. The purpose of the authors' work is to make the robot autonomously navigate in a two dimensional plane while keeping balance of its body. The control algorithm consists of three parts; the balancing and velocity control, the heading control, and the trajectory control part. The authors designed and implemented a vehicle command system for this robot with the proposed algorithm. Experiments in real world navigation have been made by using the authors' experimental system "Yamabico Kurara".>

One approach of how to pass through a doorway by a mobile robot is discussed. In this task-oriented approach, the proposed task is to realize a total behavior of opening a door and passing through a doorway for a mobile robot equipped with a manipulator. In this paper, we describe a design of such behavior, and a simulation of the behavior is shown. The key of such behavior is the cooperation between robot's function sub-systems, e.g. the locomotion control system, the manipulator control system and the sensor systems.>

A 3-D range sensor system for an autonomous mobile robot is reported. It is important for a mobile robot to recognize spaces of passage. In this sensor system, the passage space is detected with an active vision sensor using a fiber grating, laser diode, and CCD camera. The fiber grating vision sensor can easily obtain 3-D information about the object. In the authors' system, the object is the floor and the system measures the height of the floor. In this case the height is nearly equal to zero, so the robot can perceive that the measured area is passable. An image processing module using a transputer (T805) is developed for this purpose. In this paper, the principle of the sensor and the method for passage space recognition are presented. The hardware and software of the system for the authors' autonomous mobile robot "Yamabico" is presented. Experimental results are also presented.>

A path planning algorithm for mobile robotics is proposed. When a mobile robot is navigating, the error in estimated position of the robot increases in proportion to the traveling distance. Because of this error, the robot has a greater risk of collision with objects in the environment. To reduce this error, a robot should obtain environmental information by using its environment sensors, and modify its estimated position accordingly. The authors propose a cost function for the mobile robot's path which minimizes the risk of collision and an algorithm to find the optimal path and sensing points. They have implemented the proposed algorithm on a real robot system and conducted several experiments to verify it.

A control algorithm for a trailer-type mobile robot is proposed. With this algorithm, a trailer can move along a straight line and a circular arc curve both in forward and backward directions. A trailer command system which specifies the path of trailer type robot as straight lines or circular arcs has also been designed and implemented on a real experimental trailer type mobile robot. The effectiveness of the proposed control method is verified by numerical simulations and experiments using the authors' self-contained autonomous mobile robot, the Yamabico.

With a conventional ultrasonic sensor system for a mobile robot, the distance to an ob- ject can be obtained with a time-of-flight (TOF) method, in which a reflected point is regarded to be located directly on the transducer line-of- sight. However, in an indoor environment, flat walls have specular characteristics. So, the real reflected point is not located on the transducer's lime-of-sight, because an echo from the normal in- cidence only returns to the transducer, since ul- trasonic directivity is not so sharp in air. So, to accurately recognize the position of an object, it is important to detect the direction of the re- flected point. One method to obtain the direction is to calculate it from the time difference between two parallel receivers. In this paper, an ultrasonic sensing method with a wide angle and high res- olution in specular environment is proposed, and accurate environment recognition can be realized.

A vehicle command system for the wheeled autonomous mobile robot with a high capability in describing the navigation task in the real environment, is proposed. And a feedback control method to track along the given path by the vehicle commands is described. The effectiveness of the proposed vehicle command system and the trajectory control method are confirmed by numerical simulations and experiments in the real environment using a self-contained autonomous mobile robot.>

The behavior of an autonomous mobile robot must be executed based on the sensor information. The sensor-based behavior cannot be represented by a simple sequence of motions. Action mode representation and ROBOL/0 language are a powerful method to represent such sensor-based behavior. Autonomous navigation with the obstacle avoidance function is designed and represented using action modes. To show the effectiveness of the method, it is programmed in ROBOL/0 and executed on a real robot.>

The sensor with real-time environment recognition ability is one of the key technologies for autonomous robots. The authors have designed and implemented a small size optical range sensor for their experimental mobile robot. The sensor consists of a laser slit generator, a CCD image sensor and a processing unit. Using this sensor, the real-time obstacle avoiding function is realized and added to the autonomous navigation aspect of the robot.>

A wheeled mobile robot on a flat plane can estimate its current location and orientation from the cumulative wheel rotation (dead reckoning). The method, however, has the drawback that estimation errors are accumulated as the robot moves, and the accuracy of estimation decreases. To address this problem, a positioning technique using an external sensor is needed. The authors propose a more general positioning method whereby the robot can act autonomously and move along a path unlimited by positioning. The robot can modify the position estimated by dead reckoning by repeating low-level sensing asynchronously and intermittently. This method uses not only the estimated position data but also the accuracy of the dead reckoning and the external sensor effectively.>

A method is presented for modeling a robot environment and structuring its free space in terms of a set of overlapped prime rectangular areas (PRAs) which are suited for path planning and navigation tasks. Next, a connectivity table for the overlapped PRAs is constructed to provide the structure necessary for path-finding. Using the generated overlapped PRAs, a simple and computationally effective online path planning algorithm is proposed to generate the optimal collision-free path in terms of intersected PRAs from the PRA containing a start point to a PRA containing a goal point within the robot's environment. Since the movements between the PRAs cannot have fixed cost distance attached to them, an efficient technique that dynamically allocates cost to path segments as the path develops is proposed. A real-time execution algorithm is developed to control the robot during the execution of the planned path. Experimental examples based on the proposed algorithms with its results are presented for selected environments executed on the mobile robot Yamabico.M (Level-12).>

A path-description method that uses a sequence of straight lines with coordinate transformations is presented. This concept is hardware-independent and may be applied to any kind of vehicle. A local vehicle-trajectory-control algorithm is used both for determining the transient portions of each vehicle trajectory and for keeping the vehicle moving along a given directed straight line. A vehicle-control command-system, MITCHI, is one realization of the idea and is introduced. The MITCHI command-system has been implemented on self-contained Yamabico mobile robots. Several design features, such as status transition, fast/slow command execution, and velocity control, as well as simulation results, are described.>

The authors have constructed a self-contained intelligent robot on which ultrasonic range finders are installed. A sensory system with sensing ability appears necessary; the authors propose a vision system for a mobile robot that meets real time requirements. In the vision system, a color image provids actual image information and map information is also utilized for reckoning in a building environment. The key point is that matching between image and map information is performed by using highly abstracted information from the image and also from the map. The constitution of the vision system and experimental results are described.