In recent years, with the increase in physical distribution volume, unmanned transportation robots are expected as an alternative means of transporting baggage in factories and warehouses. The development of a control system for cooperative transportation by multiple robots is important when the objects to be transported are long and exceed the size and the weight limit. From this, we develop a control system for cooperative transportation using two robots independently driven by two wheels. In this paper, a communication system between two mobile robots and a host PC is constructed by using ROS, and a sub-goal is generated to each robot to realize a cooperative running with two robots. The effectiveness of the proposed method is verified through an experiment that the controlled point of an object is subject to a movement along the square of 1 m.

Demands to use washing robots in pig houses are growing up. The robot washes pig beds using a long arm over fences from passages. The passage is narrow so that the robot must detect the fences and run along the fences with high accuracy. A laser range scanner is useful to detect fences because there are many kinds of fences. However, the noises occur to the measured values if there are obstacles behind fences. In this study, the distance between scanned points and a path of robot is calculated and it is utilized with a zoned minimum filter to extract the points representing the fences. Then, the candidate lines are detected from the extracted points by Hough transform to detect multiple fences simultaneously. To run along the fences, the robot calculates the self-posture and distance to the detected fences. This paper describes the above proposed method and reports some experimental results of running along the fences and passing various intersections.

A robot with two independent driving wheels is used popularly as a service robot. Therefore, there is a lot of research on the autonomous locomotion. The robot with two independent driving wheels has a nonholonomic constraint in its model, so that it needs a specific control method when controlling it. In this research, we use an invariant manifold for solving such a nonholonomic constraint. The controller based an invariant manifold can converge the state of the controlled object to an arbitrary target position. In addition, it can also move taking account of an obstacle position by combining it with the gradient of “harmonic potential field” (HPF). On the other hand, it was confirmed in the previous research that there is the case that the robot cannot avoid the obstacle because there are not enough space to converge the state to the target state. In this paper, it is verified that the robot can converge to the target position while avoiding obstacles by dividing the target position into some pieces and moving step by step.

There are many methods for making a robot with two independent driving wheels move autonomously, but kinodynamic motion planning using HPF (Harmonic Potential Field) was seldom studied up to now. Since a nonholonomic system such as a robot with two independent driving wheels includes complicated nonlinear terms generally, it is hard to realize a stable and tractable controller design: in other words, it needs a specific control method when controlling it. However, about a dynamic control method in the motion planning, it is guaranteed that a nonholonomic controlled object can always be converged to an arbitrary point using a control method based on an invariant manifold. In this research, it is aimed at realizing kinodynamic motion planning for a robot with two independent driving wheels by combining the control based on the invariant manifold and the HPF. In this paper, how to combine the invariant manifold control and the concept of the HPF is explained in detail, and the usefulness of the proposed approach is verified through some simulations.

In this paper, kinodynamic motion planning is described for keeping the attitude of a quadrotor and converging to an arbitrary target point, while avoiding obstacles. Kinodynamic motion planning was extended for a quadrotor in our previous research, but its behavior was confirmed only in simulations. Therefore, we implement the proposed kinodynamic motion planning to an actual quadrotor, and confirm the usability of our method through basic motion experiments.

In this research, we extend the kinodynamic motion planning using “nonlinear anisotropic damping forces (NADFs),” which had been applied to a point mass in the previous research, to the motion planning of “unmanned arerial vehicles (UAVs)”. In the proposed system, we realize the autonomous locomotion for AUVs by combining the nonholonomic control, which is already established for the attitude control method, and kinodynamic motion planning. By applying this system, the control input for moving toward the given target point can be generated automatically, while keeping its altitude and attitude. In this paper, the system for controlling an X4-Flyer, which is composed of nonholonomic control and kinodynamic control, is explained. Moreover, it is confirmed in the simulation that the proposed system can guide the X4-Flyer by using the proposed method.

In this paper, a new method is proposed to realize obstacle avoidance for an autonomous mobile robot, by applying image-based control. Although many obstacle avoidance techniques are proposed until now, it is shown that it becomes possible to achieve obstacle avoidance by image-based fuzzy control, without resort to the estimation of self-position said to be indispensable in control of an autonomous mobile robot. The validity of the proposal technique is proved through real system experiments for a steered type four-wheel mobile robot.

We present a novel method to control an X4-Flyer using kinodynamic motion planning. Kinodynamic motion planning is the planning technique of generating a control input by solving the problems of kinematic constraints and dynamic constraints simultaneously, and it is useful for simpler generation of the control input. In this paper, we extend existing kinodynamic motion planning, which uses “Harmonic potential field (HPF)” and some damping forces for the control of simple point mass, to the motion planning for an X4-Flyer, which is a complex multivariable system. Then, we use “nonlinear anisotropic damping forces (NADFs),” which is proposed by Masoud, as damping force. In the simulation, a method using NADFs is compared with that using viscous damping forces. From the simulation, it is confirmed that the kinodynamic motion planning can be realized for an X4-Flyer.

In this paper, we present the tip-over prevention technique using a control moment gyro for a holonomic omnidirectional mobile robot with active dual wheel caster assemblies. With concern to the sudden dynamic changes during maneuver, the dynamical model is derived and used together with the force-angle stability measure (FASM) to estimate the tip-over incident and the tipping direction. A single gimbal control moment gyro (SGCMG) is proposed to counter the instability by producing a precession torque in the opposite direction of the estimated tip-over direction. Simulation results are given to demonstrate the performance of this approach.

In a stabilizing control for nonholonomic mobile robots with two independent driving wheels, a nonholonomic double integrator in the kinematic model is first considered as a controlled object model. Then, a quasi-continuous exponential stabilizing control method is proposed as one of underactuated control methods by using invariant manifold theory. Next, to extend the velocity input control in a kinematic level to the torque input control in a dynamical level, an extended nonholonomic double integrator consisting of the kinematic and dynamical models is treated as a controlled object model. A quasi-continuous exponential stabilizing controller is further derived for such an extended model by using the same way as used in the kinematic level control. The effectiveness of the present method is proved with some demonstrative simulations.

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.

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.

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.

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.

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.

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 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.

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.