In a teleoperated system, robots are often required to easily change among various modes of operation; further, an efficient development of large-scale teleoperated systems is desired. Thus, we propose a three-layer software architecture implemented using a database node module (DNM). All modules are connected to a DNM, with connections among modules defined as virtual connections. It is possible to change connections during operation via the virtual connection of the DNM, and the DNM can achieve high-speed communication and high-speed connection changes. We examined the evaluation index of our module design using this architecture because module interface and function design influence the architecture. Finally, we confirmed that a robot based on our architecture worked in a real environment.

For efficient wide-area exploration by an autonomous planetary rover, the generation of a global environmental map is very important. A global map is generated by matching and overlapping terrain features from digital elevation maps that are obtained during a rover traveling in a region. Each set of data contains information in different areas, and the overlapping part in each set of data may be missing data because of difference in a position and an orientation of a rover. Conventional alignment techniques based on comparing features assume that data were measured from very similar positions and orientations. Otherwise, differences in the measured region deteriorate the quality of a resulting global map. This problem should be addressed by a fairly simple way because of the limited processing capabilities of planetary exploration rovers. Hence, we propose a method for generating highly accurate global maps by considering differences in measured regions and iteratively estimating the overlapping parts in terrain data. The method is evaluated using simulated data and some experimental data obtained from experiments using a mobile robot in a real environment.

Long distance traversal by a remotely controlled rover is rendered difficult by measurement error on terrain data and communication time delays. Though an operator can select any desired path as a sequence of waypoints using a 3D terrain model evaluated by the on-board sensor, the model is error prone and the rover might collide with obstacles in its path. We present a rover that continuously updates its knowledge of the environment, and recalculates the difference between the original terrain data (used for initial path generation) and its latest acquired data. To this end, we have proposed the waypoint compensation method called Command Data Compensation (CDC) that uses the latest measurement data (assumed to be more reliable than the initial data). Such data automatically correspond to the path deviation [9] [10] [14]. In this paper, we evaluate whether CDC can help the rover safely navigate around obstacles, in terms of measure called the Safety Rate.

A new lunar exploration mission including a lander and rovers is under studying in Japan. The main mission for lunar robotics exploration is to demonstrate the technologies for lunar or planetary surface exploration. They will cover pin-point landing technology, reliable landing scheme with obstacle avoidance, landing mechanism on rough terrain, exploration rover and tele-science technology. Lunar geologic survey will be also performed to investigate the underground materials. The working group has been conducting the feasibility study of advanced technologies for lunar robotics exploration. In the rover mission, a robotic manipulator plays an important role as scientific observation tools for geological exploration. This paper proposes a light-weight manipulator with low-power consumption function. To investigate the effectiveness of the proposed design, a manipulator was developed. This paper describes a proposed smart manipulator system. This paper also presents the environment test results on Ultra-Sonic Motor. The performance of the developed smart manipulator is discussed.

Lunar rovers are required to move on rough terrains such as in craters and rear cliffs where it is scientifically very important to explore. Recently, wheel typed rovers are popular for planetary exploration missions. However, there is a problem that the wheel typed rovers have possibility of stack. Therefore, this paper investigates a mechanism of kinetic behavior between the wheels of the exploration rovers and soil. The important parameters are extracted by considering the mechanism. This paper proposes an elastic wheel by considering the important parameters. The elastic wheel has the surface which can be changed flexibly toward rough terrain. Running experiments on soil which imitated regolith are carried out to observe the traversability of the elastic wheel using slip ratio and sinkage.

Planetary exploration requires rovers to perform a variety of challenging tasks autonomously. In order to complete relevant scientific mission, these rovers need to overcome difficulty for rough terrain traversing by "online methods". This paper discusses an idea that utilizes a rover mobile center of mass in order to aid in traversing rough terrain. According to vehicle pitch angle and contact angles, the rover recalculates the optimal position for the center of mass to minimize the indicator defined by two factors : the wheel driving force over the wheel normal force (adhesion coefficient) and tip-over stability angle (stability coefficient). Two innovative approaches are developed in this paper. The first one is that the authors defines easily comprehensible two factors, adhesion and stability coefficients for traversability indicator and proposes a method to calculate optimal center of mass position. The second one is that in the case of four-wheels drive, the relation between the front wheel and the rear wheel adhesion coefficient is easily solved and the best case for giving the driving forces can be solved as force making the front and the rear wheel adhesion coefficient equal. The authors call this "optimal force distribution method". Finally, this paper shows some simulation results for traversing rough terrain that compute the optimal center of mass while traversing the terrain.

In operation environment with communication time delay, it's difficult to compose a closed loop control structure between a master and a slave system, and some scheme to achieve the stability is thus necessary. In this paper, we discuss and evaluate our proposed human machine cooperative tele-drive system that consists of global and local path-planning, for long range traversability. The operator can command any desired path as a sequence of waypoints by using a 3D terrain model measured as DEM by the on-board sensor of a rover. The data is transmitted to the ground and evaluated to obtain a dangerousness map. To cope with an unknown obstacle, a conventional autonomous path-planning algorithm is applied between each waypoint. In addition, a rover is continuously updating its knowledge about the environment. By continuously recalculating the difference between the original terrain data used for initial path generation on the ground and the most recent data acquired by the rover, a waypoint compensation can be achieved. Therefore, we have to compensate waypoints by using the latest measurement data which can be assumed more reliable than previous data, for corresponding to the difference automatically. Here, the difference is assumed as the distortion between each data set, and compensated by using a distortion compensation matrix which is the mapping between the old and new terrain data sets. Simulation and experimental results and its evaluations by using the rover test-bed are mentioned in the paper

To gather a rock, it is necessary how to get information of the surface around a sample. Usually, a surface information is brought by a special sensor such as Laser Range Finder and Stereo Camera. These sensors, however, needs more weight and power consumption and are used for only one function such as the surface measurement. And furthermore, there are some difficulties to use those sensors in some case. In this research, we propose Shadow Range Finder: SRF, which can make good use of a shadow for the measurement of a surface information under the direct sunlight. Shadow is strong for above mentioned problem, and would be recognized in the case of a halation. The measurement by SRF uses a single camera, which should be installed on a manipulator for a sampling, and a link of a manipulator, which produce its shadow. The principle of SRF is same as Laser Range Finder, and a shadow is used for scanning slit instead of a laser. In this paper, experimental results of actual objects is shown, and we discusses about accuracy of measurement data. Finally, we evaluate image thresholding method by the consideration of theoretical value at a circular light source.

In planetary exploration, when collecting a rock, it is important how to get information of the surface around a sample. Usually, surface information is brought by a special sensor such as laser range finder and stereo camera. These sensors, however, need more weight and power consumption and are used for only one function such as the surface measurement. And furthermore, there are some difficulties to use those sensors in some situation, for example, a high brightness environment. In this research, we apply Shadow Range Finder: SRF, which can make good use of a shadow for the measurement of surface information under the direct sunlight. SRF is robust for above-mentioned environment, and a shadow would be recognized in the case of a halation. The measurement by SRF uses a single camera installed on a manipulator, and a link of a manipulator, which produce its shadow. The principle of SRF is same as laser range finder, and a shadow is used for scanning slit instead of a laser. In this paper, experimental results of actual objects are shown, and we discusses about accuracy improvement for measurement data, considering an umbra and a penumbra caused by surface light source. Finally, we apply this method to tele-sampling by a manipulator on a rover system.

In this paper, we propose the Shadow Range Finder (SRF), which can make good use of shadows for the measurement of surface information under direct sunlight. The shadow is stable, and can be recognized in the case of halation. The SRF uses a single camera, which should be installed on a manipulator for sampling, and a manipulator link, which produces its shadow on a measured surface. The principle of the SRF is the same as that of a Laser Range Finder, except that a shadow is used for the scanning slit instead of a laser. In this paper, we present measurements of a real object, such as a stone, and evaluate the validity of the SRF.

This paper describes the path planning method for a planetary microrover. A planetary rover is required to travel safely over a long distance for many days in unfamiliar terrains. Hence it is very important how a planetary rover processes sensory information in order to understand the environment and to make decisions. The authors have newly developed a small rover for future lunar or planetary exploration. As a new data structure for map information, an extended elevation map is introduced, which includes the effect of the size of the rover. The proposed path planning can be conducted in such a way as if the rover were a point while the size of the rover is automatically taken into account. The map obtained by sensors includes uncertainties. Thus a path planning scheme based on traversability and probability is also proposed. The validity of the proposed method is verified by computer simulations.

We discuss a tele-driving system for distant driving of a lunar rover, and describe our newly developed small, lightweight lunar rover called Micro-5 and its visual sensor system. The operator uses a virtual world simulator to make command path. The virtual environment of this simulator is constructed with measurement data from the rover on the moon. However, there is a communication delay between the earth and the moon. So, there is a difference between the old map data which the operator used for path planning and the new data which the rover is tracking. The operator's path command is thus less reliable to avoid obstacles and to reach the goal. Therefore, to achieve a highly reliable operator's command, we propose a command-data compensation approach which compensates this difference as the distortion of the environmental map.

We discuss a tele-driving method for long-range driving of a lunar rover. An operator uses a virtual world simulator to make a command path. The virtual environment of this simulator is constructed with measurement data from a rover on the moon. We have, however, a communication delay between the earth and the moon. So, there is a difference between old map data which the operator used for path planning and new data, which a rover is tracking on. The operator's path command has less reliability for avoiding obstacles and to reach the goal. Therefore, to make the operator's command highly reliable, we propose Command-Data Compensation, which compensates this difference as the distortion of the environmental map.

In this paper we present a system that is able to give force feedback for the handling of virtual objects to a human operator and discuss how this system can learn low-level reflective behaviors from the human. A dynamic force simulator (DFS) that simulates object dynamics, contact model and friction characteristics of the human hand was developed to interact with the object in virtual reality. The DFS allows calculation and feedback of appropriate forces to the force controlled actuators of a glove type haptic interface. The measured data is used for task-teaching of the robot in the remote site. However usually the task can not be achieved by simple playback teaching. As each task execution is different due to various sources of small errors a low-level motion behavior to compensate for this errors is needed. In this paper, this function is assumed to be a reflective behavior and we acquire it by learning from human. Two learning schemes, neural nets and radial basis functions are experimentally evaluated.

In this paper we present a dynamic force simulator (DFS) for force feedback in human-machine systems. DFS simulates object dynamics, contact model and friction characteristics of the human hand interacting with the object in virtual reality. Interaction with DFS allows calculation and feedback of appropriate forces to the force controlled actuators of the sensor glove we have developed. In the future we will use this system to analyze human dextrous manipulations called human skill.

Intelligent cooperative manipulation is proposed as a new paradigm for human-machine interaction and cooperation. Aiming at intelligent assistance of human operators the information and power flow between operator-system-task environment is carefully analyzed using a virtual reality to simulate the task environment. Central issue of this virtual reality is the dynamic force simulator (DFS) for feedback force calculation proposed in this paper. The DFS simulates object dynamics, contact model and friction characteristics of the human hand interacting with objects in the virtual reality. An example shows the efficiency of the proposed realization scheme of the DFS.>

The approach presented is this paper is based on two ideas: (1) on the planning level an electrostatic potential field in the configuration space of the robot is used. The generalized force curves are attractive to the goal point avoiding obstacles without local minima; (2) on the control level the system follows these force curves using sliding mode control. The system is attracted to the swiching manifold using sliding mode and therewith the systkm is robust to disturbances and parameter variations. the system control variables so that sliding mode occurs in the vicinity of the force field curves and the system is attracted to them. This means that the system trajectories are identical to the force field curves. Sliding mode assures robust control performance despite unknown disturbances and parameter variations.