Communication robots are now getting popular. In particular, partner robots, which can perform personal services, are in high demand. However, they can be prohibitively expensive. Therefore, we considered a multi-user robot with a virtual agent service which could satisfy user demands. But, several issues need to be solved in order to achieve this purpose. Firstly, there is no general service platform for such robots. Secondly, even if we use the multi-user robot by executing the virtual agent service, the physical shape, and other characteristics of the multi-user robot sometimes creates a strong impression on users. Therefore, we proposed a virtual agent service platform, and the robot features modification for a multi-user robot. The robot can autonomously adjust its position according to each user's physiological signals, which based on emotion in real-time. We presented a preliminary evaluation to determine whether the proposed method could improve users' robot experience even for the users who are not familiar with the robot at all.

In this paper, we propose a method robustly predicting the destination of a pedestrian heading toward a robot in order to provide suitable voice guidance to him/her by communication robots installed at the reception desks of public facilities. For this purpose, we measure a pedestrian trajectory with a laser range scanner attached to the robot, and predict the destination among more than three branches by cascading multiple predictor models for two branches pre-trained by a machine learning algorithm. In order to verify the effectiveness of the proposed method, we conduct experiments using a dataset of tracking pedestrians at a shopping mall, and data observed in the real environment. The result shows that our method can predict three branch destinations with an accuracy of about 80%.

We have studied a dialog control method for interface robots by using location data of persons measured by a Laser Range Scanner as a human-robot interaction technology. In the method, we measured the distance between a sensor and a person with the sensor placed at human waist height as a time series data and estimated the position coordinates of the person at a time as a probability distribution. This paper extends the scheme and proposes a method estimating person attributes in addition to the location data by monitoring the movement of legs while the person is walking. As for person attributes, we focus on the age and classify persons as the elderly and the young. At that time, we construct a prediction model of age groups based on machine learning mechanisms. In this paper, we use seven feature values, these are the step length, the step width, the velocity of leg 1, the velocity of leg 2, the velocity of body, the acceleration of leg 1 and the acceleration of leg 2 for the model. By conducting experiments, we verify that classification accuracy improves particularly using acceleration and standard deviation of the data.

The role of the communication robot is increasing for the aging society with declining birthrate especially in Japan. Thus, field trails are very important to confirm the fundamental function of the robot and to know the comments from the person who joined the verification experiment. Here, we extended the greeting function to the interface robot ApriPocoTM considering the position and velocity of the people around the robot. The result of the verification experiment is described.

Self-localization is important for mobile robots in order to move accurately, and many works use an omnidirectional camera for self-localization. However, it is difficult to realize fast and accurate self-localization by using only one omnidirectional camera without any calibration. For its realization, we use “tracked scale and rotation invariant feature points” that are regarded as landmarks. These landmarks can be tracked and do not change for a “long” time. In a landmark selection phase, robots detect the feature points by using both a fast tracking method and a slow “Speed Up Robust Features (SURF)” method. After detection, robots select landmarks from among detected feature points by using Support Vector Machine (SVM) trained by feature vectors based on observation positions. In a self-localization phase, robots detect landmarks while switching detection methods dynamically based on a tracking error criterion that is calculated easily even in the uncalibrated omnidirectional image. We performed experiments in an approximately 10 [m] × 10 [m] mock supermarket by using a navigation robot ApriTau™ that had an omnidirectional camera on its top. The results showed that ApriTau™ could localize 2.9 times faster and 4.2 times more accurately by using the developed method than by using only the SURF method. The results also showed that ApriTau™ could arrive at a goal within a 3 [cm] error from various initial positions at the mock supermarket.

This paper describes an efficient indoor map building method that involves a robot collaborating with a human. A robot acquires the shape of a required part of an indoor environment, searches for a suitable picture from the scene of the destination, and registers it as a picture landmark at the same time as the robot follows the human. Once a picture landmark is registered on a map, a robot finds it and can self-localize from the next navigation. The validity of the proposed method is demonstrated by experiments carried out on an actual mobile robot ldquoApriAttendatraderdquo, developed by Toshiba.

A robotic transportation system for shopping support services has been developed. The system is required to act according to the customer's request and position to provide services. In collaboration with mobile robots, the system provides shopping support services.

At indoor environment, a service robot must know where it is at any time. Thus, reliable position estimation is a basic and key problem. Probabilistic robotics techniques have become one of the dominant paradigms for algorithm design in robotics. Recent work on Monte Carlo Localization with particle-based density representation becomes popular. In this paper we introduce the multi-sensor based Monte Carlo localization (MCL) method which represents a robot's belief by a set of weighted samples and use the laser range finder (LRF) sensor to measurement update. The experiment results illustrate the effectivity and robust of MCL application for our service robot.

We have developed the person following robot "ApriAttenda(TM)". This robot can accompany a person using vision based target detection and avoid obstacles with ultrasonic sensors. The robot first identifies an individual with its image processing system by detecting a person's region and recognizing the registered color and texture of his/her clothes. Our newly developed algorithm allows the robot to extract a particular individual from a cluttered background, and to find and reconnect with the person if it loses visual contact. Tracking people with vision was realized by systematizing visual and motion control with a robust algorithm that utilizes various characteristics of the image data. ApriAttenda(TM) has been exhibited at Aichi EXPO 2005, and its robust functions and smooth person following capability were successfully demonstrated.

We have developed the person following robot "ApriAttendatrade". This robot can accompany a person using vision based target detection and avoid obstacles with ultrasonic sensors while following the person. The robot first identifies an individual with its image processing system by detecting a person's region and recognizing the registered color and texture of his/her clothes. Usually, the person following robot has to detect and recognize the specified person and calculate his/her position in a complicated real-life environment of fixed objects and moving people. Our newly developed algorithm allows the robot to extract a particular individual from a cluttered background, and to find and reconnect with the person if it loses visual contact. Tracking people with stereo vision was realized by systematizing visual and motion control with a robust algorithm that utilizes various characteristics of the image data. The developed algorithm uses several analyses to extract information on the distance to each feature point, speed of target, color and texture of clothes for a stable tracking in many situations including changes of view due to self motion, shifts in lighting and objects similar to the target. The person following robot ApriAttendatrade has been exhibited at Aichi EXPO 2005, and its robust functions and smooth person following capability were successfully demonstrated

We have proposed a concept of a robotic information home appliance corresponding to one category of home robots, and developed ApriAlpha, a concept model of the robotic information home appliance. ApriAlpha is a wheel locomotion type human friendly home robot which controls advanced home appliances, standing between their users and them as a voice controlled information terminal, and offers security and information services to users. We have integrated various robot technologies such as voice communication, image recognition, planning and motion control on ApriAlpha, and we have introduced a framework of the distributed object technology based open robot controller architecture (ORCA), which we are currently developing in view of its easy extension and efficient development. This paper describes the proposed robotic information home appliance and its concept model, ApriAlpha. The functions of the developed robot are confirmed by performing several demonstrations, and the merit of applying the framework of ORCA to the home robot controller is also confirmed through its development.

Various coordinated control schemes are explored in the multi-operator-multi-robot (MOMR) tele-collaborative system through a network with time delay. Multi-robot cooperation has rapidly emerged in many possible applications such as the plant maintenance, construction, and surgery, because it would have a significant advantage over a single robot in such cases. Thus, time-delayed control of a multi-robot system is expected to play an important role in remote operations, too. However, the effect of time-delay would pose a more difficult problem to the MOMR teleoperation systems and seriously affect their performance. In this work, first, we have built an experimental system to investigate the remote cooperation in MOMR teleoperation. Then, different coordinated control methods are proposed to cope with the collision, arising from the time delay over the network. To verify the validity of the proposed schemes, we have carried out various experiments on a planar block arrangement by two slave arms employing graphic simulators and a LAN subject to a significant communication delay.

The Mechanical Engineering Laboratory (MEL) is developing technologies for multi-robot collaboration in remote environments with the Toshiba Mechanical Systems Laboratory (TMSL). Human operators' delayed visual perception due to the communication delay over the network seriously affects the collaboration performance in the multi-operator-multi-robot tele-manipulation. We have built an experimental tele-manipulation test bed connecting the MEL and the TMSL to study the time-delayed remote tele-collaboration between two places. In the test bed, one operator controls her master robot nearby two slave robots in the work site and another from a distance. A local online graphics simulator without time delay is developed to cope with the communication delay and several multi-robot coordinated control strategies are devised to avoid the collision. To verify the validity of this simulator assisted approach, we demonstrated a maintenance work on a plant mock-up in the TMSL by two different slave robots and two distant operators in the MEL and TMSL respectively through an ISDN.

Proposes task-based data exchange for teleoperation systems through a communication network as an efficient method of transmitting data between an operation device and a remote robot. On the task-based data exchange, the more important information according to the contents and conditions of the task which the robot performs is given transmission priority, for example, by altering the contents of the transmitted data. We have built an experimental system in which the master arm in Tsukuba and the slave arm in Kawasaki, separated by, about 100 km, are connected through N-ISDN and the standard techniques are utilized, such as TCP/IP, socket, JPEG, etc. A series of experimental tasks has been effectively carried out by the task-based data exchange, that is, crank operation which consists of grasping and revolution. The communication network with capacity limitations was used effectively, and the high maneuverability in real-time with bilateral servo control has been realized. The effectiveness of the task-based data exchange has been confirmed.

In this paper, remote robot collaboration using a network with communication time delay is discussed in multi-operator-multi-robot (MOMR) teleoperation. Recently, collaboration tasks have rapidly emerged in many possible applications such as plant maintenance, construction, and surgery, because multi-robot collaboration would have a significant advantage over a single robot in such cases. Problems and several noticeable results have been reported in a single-operator-single-robot (SOSR) teleoperation system. However, the effect of time-delay would pose a more difficult problem to the MOMR teleoperation systems and seriously affect their performance. In this work, first, some of the constraints on performance in MOMR teleoperation applications are examined. Then, the time-delay effects on tele-collaboration are investigated through several experimental studies. Finally, a method to cope with the time-delay in MOMR teleoperation systems is proposed exploiting the virtual thickness modification scheme.

This paper describes the development of a windshield cleaning robot system (WSC). The WSC is intended to be used for Boeing 747 aircraft parked at airports prior to service. The objects to be cleaned are spots on the windshield caused by collision with dust, insects, and birds during takeoff and landing. The WSC was developed with the objective of realizing a system which could be operated by a single operator able to complete the work on one aircraft in 10 minutes. The WSC consists of the manipulator (the arm and the cleaning device), the installation unit, the control unit, and the operation unit. A position and force control method is applied to the WSC. The target position of the arm tip is modified by using the signals from the force sensor and the joystick. In accordance with this control method, the pressure force is kept constant and the tip is moved so as to follow the shape of the workpiece. The various safety features provided include an interference limit to limit the area of movement of the arm tip. System evaluation experiments were carried out and the effectiveness of applying a lightweight manipulator with long arms to this work was confirmed.>

A new master-slave manipulator (MSM) with different configurations and different degrees of freedom (DOF) has been developed. It consists of a general master arm using pantograph mechanisms and a seven degree of freedom slave arm with a redundant joint. Symmetric bilateral control using a virtual internal model and redundant arm control with a singular configuration are used to improve the maneuverability of the MSM. The developed MSM has been confirmed to have good maneuverability from basic experiments. This paper describes the mechanisms, control methods, and experimental results of the MSM.