Shoichi Maeyama

Outdoor navigation of a mobile robot between buildings based on DGPS and odometry data fusion

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.

Non-stop outdoor navigation of a mobile robot-retroactive positioning data fusion with a time consuming sensor system

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.

Rule based filtering and fusion of odometry and gyroscope for a fail safe dead reckoning system of a mobile robot

For mobile robot behavior such as navigation and map building, the estimation of own position is very important. Odometry is often utilized for the position estimation by accumulating the amount of wheel rotations. In outdoor environment, the estimated position by odometry has not only the cumulative error but also occasional error by traveling over a small obstacle or a bump under the wheel. In this paper, we propose accurate and robust dead reckoning system by fusion and filtering with odometry and gyroscope. The proposed dead reckoning algorithm can reduce the ill-effect of road surface, estimate the bias drift of gyroscope and warn a failure of sensor. It would work very well in outdoor as well as indoor environment.

Field Experiment on Multiple Mobile Robots Conducted in an Underground Mall

Rapid information gathering during the initial stage of investigation is an important process in case of disasters. However this task could be very risky, or even impossible for human rescue crews, when the environment has contaminated by nuclear, biological, or chemical weapons. We developed the information gathering system using multiple mobile robots teleoperated from the safe place, to be deployed in such situation. In this paper, we described functions of the system and report the field experiment conducted in a real underground mall to validate its usability, limitation, and requirements for future developments.

An implementation of landmark-based position estimation function as an autonomous and distributed system for a mobile robot

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.

Underactuated control for nonholonomic mobile robots by using double integrator model and invariant manifold theory

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.

Estimation of human behaviors based on human actions using an ANN

An approach to human behavior recognition is presented in this paper. The system is separated into two parts: human action recognition and object recognition. The estimation result is composed of a simple action “Pointing” and a virtual assumed object, which has two attributes, one is “current status” and the other is “acceptable behavior”. Once the human action and object are recognized, then detect whether a vector calculated by human elbow intersected the object. If the vector is intersected, then estimate human behavior by combining the human action and the object attribute. The artificial neural network (ANN) is discussed as a main part of the current research. Whole ANN processing is simulated by Octave 3.8, the human actions are captured by Microsoft Kinect, and a human model is built by using human joint data.

A mobile robot campus walkway following with daylight-change-proof walkway color image segmentation

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.

Kinodynamic motion planning and control for an X4-Flyer using anisotropic damping forces

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.

Image-based fuzzy trajectory tracking control for four-wheel steered mobile robots

A four-wheel steered mobile robot is fit for a higher power or improvement in the movement speed of a robot than a two-independent wheeled one. Since a steered mobile robot that slips very often cannot apply a popular dead-reckoning method using rotary encoders, it is desirable to use external sensors such as cameras. This paper describes a method to trace a straight line for four-wheel steered mobile robots using an image-based control method. Its controller is designed as a fuzzy controller and evaluated through some simulations and real robot.