This paper describes an efficient symbolic model checking algorithm for verification of deadlock free property of high level robot control program called Task Control Architecture (TCA). TCA is a model of concurrent robot control processes. The verification tool we used is the Symbolic Model Verifier (SMV). Since the SMV is not so efficient for verification of liveness properties of many concurrent processes such as deadlock free property, we first described the deadlock free property by using safety properties that SMV can verify efficiently. In addition, we modify the symbolic model checking algorithm of the SMV so that it can handle many concurrent processes efficiently. Experimental measurements show that we can obtain more than 1000 times speed-up by these methods.

This paper addresses a high-order sliding mode control strategy for output tracking of nonholonomic mobile robots. First, we introduce the dynamic model of robots, driving motors and nonslipping kinematics constraint conditions. Second, we decompose the system into linear and nonlinear components via diffeomorphism and nonlinear input transformation. Also we consider parameter variations of robots and deduce the uncertain model of robots. Third, we design a high order sliding mode controller for output tracking of known and uncertain systems, respectively. Finally, we perform numerical simulations, demonstrating that the proposed high-order sliding mode control not only reduces the chattering problem of sliding mode systems, but also has certain robustness properties with respect to uncertainties of robots.

Incremental evolution with learning (IEWL) is proposed for the development of autonomous robots, and the validity of the method is evaluated with a real mobile robot to acquire a complex task. Development of the control system for a complex task, i.e., approaching toward a target object by avoiding obstacles in an environment, is incrementally carried out in two-stage. In the first-stage, controllers are developed to avoid obstacles in the environment. By using acquired knowledge of the first-stage, controllers are developed in the second-stage to approach toward the target object by avoiding obstacles in the environment. It is found that the use of learning in conjunction with incremental evolution is beneficial for maintaining diversity in the evolving population. The performances of two controllers, one developed by IEWL and the other developed by incremental evolution without learning (IENL), are compared on the given task. The experimental results show that robust performance is achieved when controllers are developed by IEWL.

This paper presents the concepts and methodology of knowledge-based information modeling based on Cognitive Science for realizing the autonomous humanoid service robotic arm and hand system HARIS. The HARIS robotic system consists of model-based 3D vision, intelligent scheduler, computerized arm/hand controller, humanoid HARIS arm/hand unit and human interface, and aims to serve the aged and disabled on desk-top object manipulations. The world model, i.e., a shared knowledge base, is introduced to work as a communication channel among the software modules. The task scheduling as well as the 3D-vision is based on Cognitive Science, i.e., a human's way of vision and scheduling is considered in designing the knowledge-based software system. The key idea is to use "words" in describing a scene, scheduling tasks, controlling an arm and hand, and interacting with a human. The world model plays a key role in fusing a variety of distributed functions. The generalized frame-based knowledge engineering environment ZERO++ has been effectively used as a software platform in implementing the system. The experimental system is working within a limited situation successfully. Through the introduction of Cognitive Science-based information modeling we have learned useful hints for realizing human-robot symbiosis, that is our long term goal of the project.

In order to navigate a mobile robot or an autonomous vehicle in indoor environment, which includes several kinds of obstacles such as walls, furniture, and humans, the distance between the mobile robot and the obstacles have to be determined. These obstacles can be considered as walls with complicated edges. This paper proposes a mobile-robot-navigation method by using the polar coordinate transformation from an omnidirectional image. The omnidirectional image is obtained from a hyperboloidal mirror, which has the prominent feature in sensing the surrounding image at the same time. When the wall image from the camera is transformed by the transformation, the straight lines between the wall and the floor appear in the curve line after transformation. The peak point represents the distance and the direction between the robot and the wall. In addition, the wall types can be classified by the pattern and number of peak points. They are one side wall, corridor and corner. To navigate the mobile robot, in this paper, it starts with comparing a peak point obtained from the real image with the reference point determined by designed distance and direction. If there is a difference between the two points, the system will compute appropriate wheel angle to adjust the distance and direction against the wall by keeping the peak point in the same position as the reference point. The experiments are performed on the prototype mobile robot. The results show that for the determining distance from the robot to the wall between 70-290 cm, the average error is 6.23 percent. For three types of the wall classification, this method can correctly classify 86.67 percent of 15 image samples. In the robot movement alongside the wall, the system approximately consumes the 3 frame/s processing time at 10 cm/s motion speed. The mobile robot can maintain its motion alongside the wall with the average error 12 cm from reference distance.

The paper proposes a vision-based system for adaptively inferring the interactional intention of a person coming close to a robot, which plays an important role in the succeeding stage of human/robot cooperative handling of works/tools in production lines. Here, interactional intention is ranged in the meaning of the intention to interact/operate with the robot, which is proposed to be estimated by the human head moving path during an incipient period of time. To implement this intention inference capability, first, human entrance is detected and is modeled by an ellipse to supply information about the head position. Second, B-spline technique is used to approximate the trajectory with reduced control points in order that the system acquires information about the human motion direction and the curvature of the motion trajectory. Finally, Hidden Markov Models (HMMs) are applied as the adaptive inference engines at the stage of inferring the human interactional intention. The HMM algorithm with a stochastic pattern matching capability is extended to supply whether or not a person has an intention toward the robot at the incipient time. The reestimation process here models the motion behavior of an human worker when he has or doesn't have the intention to operate the robot. Experimental results demonstrate the adaptability of the inference system using the extended HMM algorithm for filtering out motion deviation over the trajectory.

A general tracking control problem for mobile robots is proposed and solved using the backstepping technique. A global result is given for the kinematic steering system to make the tracking error approaching to zero asymptotically. Based on our efforts, the proposed controller can solve both the tracking problem and the regulation problem of mobile robots. In particular, mobile robots can now globally follow any differentiable with bounded velocities path such as a straight line, a circle and the path approaching to the origin using the proposed controller. Moreover, the problem of back-into-garage parking is also solved by our approach. Some interesting simulation results are given to illustrate the effectiveness of the proposed tracking control laws.

This paper is concerned with analysis of nonlinear dynamics under geometric constraints that express pinching motions of a pair of multi-degrees of freedom fingers with soft tips. The dynamics of such a pair of soft fingers can be expressed by a set of complicated nonlinear differential equations with algebraic constraints, even if the motion is constrained in a plane. However, it is shown from the passivity analysis that dynamic stable grasping (pinching) can be realized by means of a feedforward input of desired internal force with coefficients composed of elements of Jacobian matrices plus a feedback of the difference between moments of rotation exerted at both sides of the object. It is shown in the case of a pair of 2 d.o.f. and 3 d.o.f. fingers (corresponding to a pair of thumb and index fingers) that a principle of linear superposition is applicable to design of additional feedback signals for controlling simultaneously the posture (rotational angle) and position of the mass center of the object, though the dynamics are nonlinear. A sufficient condition for applicability of the principle of superposition is discussed and given as a condition for unique stationary resolution of the overall motion to elementary motions (stable grasping, rotation control, x and y coordinates control). The principle implies that a skilled motion can be resolved into some of elementary motions which human can learn separately and independently.

A hybrid system in which mobile terminals (MTs) themselves select whether to communicate directly or via base stations (BSs) from communication conditions, "cellularad-hoc united communication system," has been proposed by the authors. It has been confirmed to have effective channel usage and battery consumption, especially for MTs which tend to communicate with partners which are close together, such as operational mobile robots. In this paper, the hybrid system is examined with respect to handoff rate. This hybrid system uses two modes, a cellular mode and an ad-hoc mode. The former mode is for communication using BSs and the latter is for direct communication. Thus, there will be two kinds of handoffs. One is the ordinary one between BSs and the other is between the two modes. Such a system may suffer from frequent handoffs. Thus the handoff rate of the system was examined. However, by the addition of a simple hysteresis characteristic, the handoff rate was held down closer to that of a pure cellular system in a multipath environment.

In industrial assembly lines, seam sealing is a painting process used for making watertight seals or for preventing rusting. In the process, sealant is painted on seams located at the joints of pressed metal parts. We developed a sealing robot system that adjusts the sealing gun motion adaptively to the seam position sensed by a range sensor (a scanning laser rangefinder which senses profile range data). In this paper, we propose a high-speed and highly reliable algorithm for seam position computation from the sensed profile range data around the seam. It is proved experimentally that the sealing robot system used with the developed algorithm is very effective, especially for reducing wasted sealant.

Two types of biomimetic chemical sensing systems are reviewed. One is an electronic nose and tongue which can recognize odor or taste from the output pattern of arrayed chemical sensors with different but overlapped specificities. The other is a chemical plume tracing system which has been developed to mimic the moth behavior in tracing the sexual pheromone from a female. We have created an odor/gas tracing robot and a compass, both of which can detect the direction from which an odor/gas is issuing.

In visual servoing, most studies are concerned with robotic application with known objects. In this paper, the problem of controlling a motion by visual servoing around an unknown object is addressed. In this case, the approach is interpreted as an initial step towards a perception goal of an unmodeled object. The main goal is to perform motion with regard to the object in order to discover several viewpoint of the object. An adaptive visual servoing scheme is proposed to perform such task. The originality of our work is based on the choice and extraction of visual features in accordance with motions to be performed. The notion of invariant feature is introduced to control the navigational task around the unknown object. During experimentation, a cartesian robot connected to a real time vision system is used. A CCD camera is mounted on the end effector of the robot. The experimental results present a linkage of desired motion around different kind of objects.

This paper presents a novel technique for analyzing and designing local communication systems for distributed mobile robotic systems (DMRS). Our goal is to provide an analysis-base guideline for designing local communication systems to efficiently transmit task information to the appropriate robots. In this paper, we propose a layered methodology, i. e. , design from spatial and temporal aspects based on analysis of information diffusion by local communication between robots. The task environment is classified so that each analysis and design is applied in a systematic way. The spatial design gives the optimal communication area for minimizing transmission time for various cooperative tasks. In the temporal design, we derive the information announcing time to avoid excessive information diffusion. The designed local communication is evaluated in comparison with global communication. Finally, we performed simulations and experiments to demonstrate that the analysis and design technique is effective for constructing an efficient local communication system.

Designing control and robotic systems as autonomous decentralized systems introduces a new degree of flexibility in the manufacturing and in the application of such systems. This flexibility is required for the systems to work in environments that are not totally predictable and that can change dynamically. In this paper, we present a new concept for real-time communication that supports this flexibility while still preserving real-time guarantees for hard real-time communication. The concept is designed to work on multiple-access busses. In particular, we consider its application on wireless local area networks and field-busses. The concept addresses requirements of hard-real time, soft real-time and non real-time communication. For this, we extend the TDMA (time- division multiple-access) approach for time-triggered hard-real time communication by the concept of shared channels that support event-triggered communication and coexist with hard real-time channels. A first implementation of concept has been carried out in the context of the CAN-bus.

Building robots is generally considered difficult, because the designer not only has to predict the interactions between the robot and the environment, but also has to deal with the consequent problems. In recent years, evolutionary algorithms have been proposed to synthesize robot controllers. However, admittedly, it is not satisfactory enough just to evolve the control system, because the performance of the control system depends on other hardware parameters -- the robot body plan -- which might include body size, wheel radius, motor time constant, etc. Therefore, the robot body plan itself should, ideally, also adapt to the task that the evolved robot is expected to accomplish. In this paper, a hybrid GP/GA framework is presented to evolve complete robot systems, including controllers and bodies, to achieve fitness-specified tasks. In order to assess the performance of the developed system, we use it with a fixed robot body plan to evolve controllers for a variety of tasks at first, then to evolve complete robot systems. Experimental results show the promise of our system.

We discuss optimal estimation of the current location of a mobile robot by matching an image of the scene taken by the robot with the model of the environment. We first present a theoretical accuracy bound and then give a method that attains that bound, which can be viewed as describing the probability distribution of the current location. Using real images, we demonstrate that our method is superior to the naive least-squares method. We also confirm the theoretical predictions of our theory by applying the bootstrap procedure.

This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and on-line motion planning. We first presents a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are shown. Then, we discuss an extension of the GA for solving both path planning and trajectory planning simultaneously.

A communication system which attains an efficient amalgamation of base station (BS) type cellular communication and non-BS type direct communication for mobile terminals (MTs), "cellularad-hoc united communication system," is proposed. In this system, whether a cellular system or an ad-hoc communication system is chosen by distance and whether the condition is good or not between communicating MTs. In other words, when two terminals are relatively near each other and are in sufficient conditions to communicate directly, they select the ad-hoc communication, while for other cases they use the cellular system. The proposed system was confirmed to have effective channel usage and low battery consumption from the simulation results. It can be also said that this system is suited especially for MTs which tend to communicate with closer partners such as operational mobile robots and autonomous carrier vehicles.

Presently, mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. These systems each have their strengths and weaknesses. For example, although the visual system enables a rich input of data from the surrounding environment, allowing an accurate perception of the area, processing of the images invariably takes time. The sonar system, on the other hand, though quicker in response, is limited in terms of quality, accuracy and range of data. Therefore, any navigation methods that involves only any one system as the primary source for navigation, will result in the incompetency of the robot to navigate efficiently in a foreign, slightly-more-complicated-than-usual surrounding. Of course, this is not acceptable if robots are to work harmoniously with humans in a normal office/laboratory environment. Thus, to fully utilise the strengths of both the sonar and visual sensing systems, this paper proposes a fusion of navigating methods involving both the sonar and visual systems as primary sources to produce a fast, efficient and reliable obstacle-avoiding and navigating system. Furthermore, to further enhance a better perception of the surroundings and to improve the navigation capabilities of the mobile robot, active sensing modules are also included. The result is an active sensor fusion system for the collision avoiding behaviour of mobile robots. This behaviour can then be incorporated into other purposive behaviours (eg. Goal Seeking, Path Finding, etc. ). The validity of this system is also shown in real robot experiments.

The majority of independent locomotion microrobots pack batteries as their energy source. However, because the energy that can be stored in a battery is proportional to its volume, the operating time becomes shorter as the robot becomes smaller. To solve this problem the energy must be supplied from outside by wireless transmission. We propose a microwave energy transmission system for microrobots in metal piping. Because microwave is rectified and converted in the form of electric energy in this system, we developed a receiving antenna for microrobots in piping and a microwave rectifying circuit to generate high voltage. These were loaded on a microrobot, tested to drive a locomotive mechanism, and the efficiency of the proposed system was confirmed.