竹囲 年延

The construction industry faces a labor shortage problem, so construction vehicles need to be automated. For automation, a position estimation method is expected that is independent of the work environment and can accurately estimate the position of targets. This paper aims to develop a position estimation method for multiple construction vehicles using 3D LiDAR installed in a work environment. By focusing on the shape of construction vehicles, this method can estimate the location of construction vehicles in places where conventional methods cannot be used, such as valleys or roofs. Because the shape of the construction vehicle changes depending on the work equipment and steering operation, each joint angle was obtained, and the 3D model used for estimation was updated. As a result of the experiment, it was verified that the position and orientation of multiple construction vehicles can be estimated with an accuracy that satisfies the required accuracy.

Localization methods for autonomous construction vehicles include real-time kinematic positioning through a global navigation satellite system (GNSS) and a scan matching with a light detection and ranging (LiDAR) attached to mobility. However, these conventional methods have low estimation accuracy when the vehicle's surroundings have few features and the vehicle is in the no-GNSS area. For the estimation in such areas, this paper proposes a localization method that can estimate by matching a 3D model of a construction vehicle with a point cloud obtained from 3D LiDARs installed in a work area. To realize the high-accuracy and high-speed processing of the localization, we propose remodeling using the predictive motion model (RM) algorithm to modify the 3D model in the registration process. In the experimental results on rough terrain, we confirmed that our method can estimate a vehicle's position and yaw angle with accuracies of 0.121 m and 0.016 rad, respectively. In addition, compared with the case without the RM algorithm, the construction vehicle's position and yaw angle accuracies improved up to 5 and 12 times, respectively.

We propose a remote joint impedance estimation system called Tele-snap for a rehabilitation diagnosis under the COVID-19 pandemic. Dynamic resistance of the human joint is essential physical information reflecting the motor function. The resistance is assessed based on the touching sensation of the doctor (physiotherapist), but the pandemic restricts such an in-person manner. Our proposing system aims to provide this physical information quantified by the joint impedance for a diagnosis in the telerehabilitation context. The proposed system employs a compact impulsive perturbation generator called the snap motor and a marker-less motion capture technology called the OpenPose. The subsystem installed in the patient's place is then simplified remarkably, which consists of the wearable snap motor and Raspberry Pi with a built-in camera module. The proposed system can collect the dataset for impedance estimation through the examiner's teleoperation of the snap motor and camera via a virtual private network, with no need for the operation by the patient. We verify the proposed system through an in-person experiment and then demonstrate the remote impedance estimation scheme.

This study introduces expedite the complete transfer of distributed gravel piles with an automated wheel loader. The wheel loader scoops the gravel and unloads it onto the bed of a truck. The total mileage for the repeated scooping and unloading work is reduced. The complicated optimal task is divided into three simple, organized subjects and different appropriate algorithms are used for each subject. A method is proposed that interactively selects the appropriate scooping points, unloading points, and appropriate path for the varying shape of the gravel pile until all gravel piles have been scooped up. To expedite the complete transfer of distributed gravel piles, the deep reinforcement learning model, trained via simulation, can be used in practice by implementing as part of the proposed methods. This paper describes these issues and the proposed methods. The performance of the actual application is demonstrated in terms of the calculation time and the feasibility of the simulations.

This letter proposes a scanning tactile sensor that amplifies the signal output of a strain gauge deformed into a wave shape and fixes the position of micro defects. In this study, we realized a thin scanning tactile sensor that is sensitive to micro bumps and can be used as artificial skin. The proposed scanning sensor consists of a simple flexible structure and a strain gauge. The inspection time needed to detect a convex shape from a wide area on a plate can be shortened by using a long strain gauge. However, the output signal is weak, making it difficult to identify the position. Parallel pins placed on the sheet increase the deformation of the strain gauges and amplify the output. We conducted an experiment to compare the output signals of the proposed sensor and a tactile sensor with strain gauge attached to a silicon sheet. Compared with a silicon tactile sensor, the output of the proposed tactile sensor on a curved surface was amplified by about 4.7 times. In addition, the output signal for a small convex shape (50 mu m in height) was amplified about 4 times more than that of the simple strain gauge. We can easily detect micro bumps from the signal of the proposed sensor. Finally, we combined two of the proposed sensors to conduct an experiment to detect the position of micro bumps. The position of a convex micro deformation with a height of 50 mu m was precisely identified.

Many cooking robots have been developed in response to the increasing demand for such robots. However, most existing robots must be programmed according to specific recipes to enable cooking using robotic arms, which requires considerable time and expertise. Therefore, this paper proposes a method to allow a robot to cook by analyzing recipes available on the internet, without any recipe-specific programming. The proposed method can be used to plan robot motion based on the analysis of the cooking procedure for a recipe. We developed a cooking robot to execute the proposed method and evaluated the effectiveness of this approach by analyzing 50 recipes. More than 25 recipes could be cooked using the proposed approach.

We found that a spiral coil placed beneath a fingertip enhances tactile sensation while tracing small undulated surfaces. Hence, we investigated the mechanism underlying the enhanced tactile sensation. We evaluated the amplification effect quantitatively to demonstrate that the coil increases the tactile sensation in the finger pad. Specifically, we installed a strain gauge between the spiral coil and the fingertip to measure the strain corresponding to the curvature of a skin surface that undergoes deformation when tracing the surface. Then, to determine the enhancing mechanism of tactile sensation by the coil, we modeled the coil while moving on a surface with irregularities. The corresponding simulation results show that the inclination of the coil elements changes while moving on uneven shapes. Furthermore, as the distance between the tips of adjacent coil elements increases (reduces), the shape (or curvature) of the skin varies, and the skin on the fingertip attached to the coil expands (contracts) along the lateral direction. Therefore, the lateral strain on the fingertip is amplified by the coil moving on an undulated surface, thus enhancing tactile sensation.

In recent years, users of online shopping have been increasing. Along with this, problems such as shortage of staff of a delivery company and the long working hours have occurred, and the burden on the delivery company is increasing. As a solution to the problem, development of a transfer robot adapted to various delivery environments is expected. In this study, we develop a half-drone wheeled inverted pendulum robot that integrates a wheel and a drone. This robot can travel efficiently in both flat plane and narrow steps without severe restrictions on the load capacity and cruising distance. This paper describes experimental results in position control on the inverted pendulum mode to verify fundamental performance of the first prototype robot.

Cooking robots still have problems, such as poor the cooking performance, unsatisfactory methods for executing recipe instructions, and the large scale of the system. The objective of this study is to develop a cooking robot that can improve cooking performance while reducing the scale of the system. In this paper, we propose a tower-type cooking robot that functions as a single, small-scale cooking robot system by layering individual cooking mechanisms as units and stacking them together. In addition, we apply our recipe analysis algorithm to the proposed tower-type cooking robot to solve the problem of executing recipe instructions. To achieve our objective, we have developed a prototype of a tower-type cooking robot and an experiment. Since the improvement in cooking performance is dependent on each unit, we will have to improve their controls and mechanisms in the future.

We propose a wheeled stilts-type personal micro-mobility. The mobility itself is a form with a wheel on the lower end of a pole-shaped handle, which is used as one mobility in pairs. The user holds the pole-shaped handle on each side in hand and stands on step attached over the wheels with both legs. The two mobilities are completely separated, and the appearance of getting on the mobility is similar to "stilts". The mobilities move while being inverted pendulum by applying the inverted pendulum control to each left and right body. In this work, we have developed a mobility mechanism prototype with low height-tubular wheels in the drive unit and conduct basic driving experiments. We report the findings and problems from the experiment of flat surface running.

In this paper, we propose a wearable tactile sensor for measuring the shape of micro-undulations on a hard surface. The proposed sensor has two layers. The inner one is a thin rubber layer into which a strain gauge is embedded that is formed around a user's finger. The outer layer is a flexible structure that consists of numerous pins on a flexible sheet. The shape of micro-undulations on an object surface can be measured when a user wearing the sensor traces the surface. The results of an experiment, in which we compare the cases with and without the flexible structure of the sensor, show that our proposed sensor is sufficiently accurate to measure the shape of micro-undulations due to its flexible structure, which contributes significantly to improving its signal-to-noise ratio.

This paper presents a method to generate actual motions and its procedure for cooking robot equipped one robotic arm by interpreting Japanese letter recipes posted on general cooking-website for human-cooking. The cooking-recipes obtained from those website includes not only the material of cooking and the procedure of the cooking but also several redundancies such as impressions of the author. Furthermore the recipe includes a pre-processing method, but it is not written explicitly. Therefore, words in the recipe are classified, encoded and rearranged properly then motion codes which are suitable for the movements of the arm and procedures in according to the intention of the author are generated. The feasibility of the method was confirmed by simulator and actual machine experiments.

In this study, a simulation of a real-time surface undulation detection system based on machine learning techniques was developed. In this system, surface undulations are sensed using a sensor called the "strain-gauge-sandwiched rubber artificial skin layer," and the digitized undulation data are processed by fast Fourier transform and input into a single-layer neural network. Preliminary results suggest that the proposed system is capable of discriminating convex deformations ranging from 0 to 60 mu m in height.

We propose a method to intuitively give the target traveling route for the snow removal autonomous mobile robot. That is, the user moves with RTK-GNSS of one frequency, and the user registers its trajectory using the smartphone, thereby setting the trajectory as the target traveling route of the mobile robot. The most important issue in this method is to reduce the error of position information obtained from the floating-point solution of RTK-GNSS obtained in the environment surrounded by the building. To solve the problem, we propose a method to correct the position of a user with RTK-GNSS only once by using the laser range sensor installed in the robot when the user starts route generation. In this paper, we describe the proposed system and method and show its effectiveness through experimental results.

This paper proposes a wearable haptic sensor for the reconstruction of the surface geometry of an object to be touched. The proposed haptic sensor is a thin rubber artificial skin layer that is formed around the user's finger or other body part and contains a small embedded strain gauge for measuring large deformations. The sensor can be easily fabricated by rubber dipping. First, it was demonstrated that the proposed sensor is not only able to statically detect the curvature of the touched surface but can also measure deformations due to rapid light tapping with robustness against motion noise. As an illustrative demonstration of morphological computation in haptics, it was then demonstrated that it is possible to reconstruct the geometry of tiny undulations in the surface of the touched object from the information obtained by the proposed sensor.

In this paper, we report a haptic phenomenon observed by combined use of two haptic devices, which are a rubber artificial skin layer with a strain gauge and a tactile contact lens (TCL). The rubber artificial skin layer with a strain gauge is a tactile sensor formed around a finger. The sensor can observe deformation of a finger wearing it by active touch. The TCL is a non-mechatronic touch enhancing device. The TCL makes tactile perception of a surface undulation enhance when the TCL is traced a surface of a tactile target and laid between human skin and the surface traced. We prepare a haptic display using a McKibben rubber pneumatic actuator which is driven according to the sensor output for a demonstration.

An increase in the number of wind turbines for power generation increases necessary inspection and repair work. Specifically, inspection and repair of the leading-edge part of the blades is severely required, and the number is also high. Inspection and repair work is dangerous and costly. Therefore, we propose a novel robot that can move in a vertical direction by using the blade as a guide while touching the leading-edge of the wind turbine blade. This method involves ensuring that the size of the robot is sufficiently small to be transported by humans, and the robot is controlled in a simple way by only using existing facilities, and thus, it is possible to perform contact work.

This paper introduces an effect of tactile contact lens (TCL) on a rubber artificial skin layer with a strain gauge. The TCL is a non-mechatronic touch enhancing device. The TCL makes tactile perception of a surface undulation enhance when the TCL is traced a surface of a tactile target and laid between human skin and the surface traced. The rubber artificial skin layer with a strain gauge is a tactile sensor formed around a finger. The sensor can observe deformation of a finger wearing it by active touch. We have found a phenomenon that the sensor output is enhanced when a finger wearing the sensor and the TCL trace undulation surface. We evaluate an effect of the TCL on the sensor using the phenomenon.

The authors have developed the autonomous loading system by wheel loader. In this paper, we propose the path planning algorithm to optimally place both one unloading point and a set of several scooping points corresponding to that point. For simultaneously determining the set and streamlining the whole series of operations, this algorithm include the step of estimating the shape of rock piles collapsing by scooping works.

Recently autonomous navigation technique for a mobile robot becomes very important. In a field of navigation, the technique for localization and mapping by laser range finder is one of the major interesting topic. In order to use the method, an environment map including navigation root is need to be prepared in advance. Then, it is necessary to travel the route once before to make the map and the route by a mobile robot which performs the autonomous navigation. In many cases, when collecting environmental data, the robot requires a person to be accompanied. When making a wide range of environmental map, the person needs to walk long distance, and the load of the person increases. Therefore, we suggest to use bicycle installed LIDER and ride it to get the information of environment of the map. By using the bicycle, it is considered that the cost and time to collect the information of environment becomes low and short. In this work, we report an experiment of mapping in riding a bicycle equipped with a laser range finder, gyro sensor and encoder, and an experiment of a navigation by a mobile robot with the map created by the bicycle.

The authors have developed an autonomous loading system for a wheel loader. In this paper, an algorithm is proposed to decide on both an optimized unloading point and several paths between the unloading point and several scooping points. The optimal unloading point that minimizes the total length of those paths has been obtained by using a three-dimensional configuration score space. In the configuration score space, the length of the route from origin to each grid is represented as score number, and a grid shows a position(x,y) and posture(theta). This method was evaluated through simulations and by experiments using a miniature wheel loader robot.

We have developed a wearable mobility and the interface to control the mobility, which is operated according to motions of lower legs of a wearer with the mobility. They are small wheeled mobile robots, which are mounted at sole of the both feet. In this paper, we introduce the developed mobility and propose a new interface to handle the mobility instinctively for the wearer with the mobility. Then, in experiments we show that it is can easy to perform following motions with the mobility, going front and backward motion, walking motion, turn, going up/down in the step motion, and striding over some obstacles.

Recently, e-assessment has become popular, and it is now technically possible for people to take exams at home. However, because the testing environment is dramatically different from the traditional one, new technologies are required to prevent cheating. Many studies have addressed testing environments where a keyboard and mouse are used as input devices, but few have focused on an environment using tablet computers, which are widespread nowadays. The aim of our study is to develop a method of detecting impersonation using touch gestures on a tablet computer. We verified that tap gestures performed by different people on a tablet computer can be distinguished by extracting some features from finger tapping images. An experiment using 30 subjects was conducted for verification.

There is a demand of mining automation by heavy equipment in an open mine. Authors aim to automization of motion for wheel loader in scooping and loading operation. In this paper, we applied the optimization method by Genetic Algorithm to the path planning for the wheel loader on scooping and loading operation. We showed the quasi-optimized path and demonstrated by the miniature wheel loader robot.

We propose the robust 2D localization applies an Auxiliary Particle Filter (APF) to Monte Carlo Localization (MCL). Urban environments have fewer landmarks than two-dimensional (2D) indoor maps for efficiently finding a unique location. Localization using MCL have the problem that few landmarks pose divergence of the particles of MCL. We use APF for MCL, because APF continues resampling until convergence particle occurs in one localization step. Another problem with 2D urban mapping is that of data association posed by three-dimensional (3D) surfaces. Pitching and rolling may, for example, adversely affect 2D scan-data metrics due to 3D surfaces, causing mismatching data association in 2D maps. We therefore use a Laplacian filter for 2D grid maps. Experimental results show that our localization method is more highly stable in urban environments than MCL.

The objective of this research is to perform a long distance navigation in indoor environment, with a unicycle robot that has a wide-type wheel, and has a laser range finder installed on top of the robot. At present, there is no report for long distance navigation by unicycle robot in real indoor environment. We have developed a system that consists of two subsystems; "Balancing and Maneuvering System" for moving robot to desired direction while the posture of the robot is stabilized, and "Navigation System" for calculation of desired direction and recognition of intersections, using external sensor whose scan plain changes when robot steers. We have implemented the system to a single SH-4 CPU microcomputer, and performed a long distance navigation in actual indoor environment. The paper reports the unicycle robot and the system we have developed, and the experiment result of long distance navigation in indoor environment.

Our purpose is to develop a simulator to emulate movements of a real small sized bike robot under feedback control.(1) We configured the bike robot model by using 4 simple rigid links and derived motion equations for the bike robot from simple constraints among those links. Simple viscus friction is considered in the simulator. We compared the results of the simulations with the movements of the real bike robot under the same feedback control algorithm and the same control coefficient with the bike robot. We confirm that the results of the simulations are almost similar to the motions of the bike robot on the whole. In this paper, we report that our bike-robot model, the simulator and the simulation results compared with the motion of the real robot. We consider it is sufficient to simulate a motion of the bike robot.

Our goal is to configure an automatic baggage-transportation system by an inverted pendulum robot and realize a navigation function in a real environment. The system consists of two cooperative subsystems: a balancing-and-traveling control subsystem and a navigation subsystem. Position errors of the inverted pendulum robot are often caused by a drift error in the gyro sensor and a change in the center of gravity by a loaded baggage when applying the linear state feedback control method for balancing and traveling. We have reduced the position errors for navigation by resetting the balance position occasionally while traveling with simple methods without an external observer or alternative sensors. In this paper, we state the method and show the experimental results of navigation in a real environment by the implemented robot system.

We are developing a human-riding wheeled inverted pendulum for use as a personal vehicle. To be practically usable, the vehicle requires a function that enables the rider to get on and off both safely and smoothly while on a slope of unknown angle. Concretely, for the convenience of the rider, the vehicle needs to be stabilized on an unknown slope without the rider aboard, both before the rider gets on it and after he/she gets off it. Moreover, the vehicle should be stabilized safely relative to the rider's handling force at a grip of the vehicle while getting on and off. We thus developed a method of estimating the handling force and the slope angle separately. In this paper, we report the method to estimate the handling force and the slope angle using a disturbance observer. We verified the validity of our proposed estimation method by computer simulations and experiments using a prototype of a human-riding wheeled inverted pendulum on an unknown slope.

Our goal is to configure a baggage transportation system by an inverted pendulum robot and realize an navigation system. The system is consisted from two sub-systems, one is balancing-and-running control system, and the other is the navigation system, and they work with each other. In this paper, we state those systems and show some experiments for that.

A target of our research is a conected two-pole-link mechanism with one controllable joint. The one link is long and the another one is short. The long link is jointed to the center of the short link with an actuated joint. We call the long link upper-body, and the short one lower-body. In initial condition, upper-body stands vertically and lower-body lies on the ground. This mechanism is expected to be able to move by swinging its upper body and rolling its lower-body, from that initial posture. In this paper, we propose some control laws and algorithms, for the model of this underactuated mechanism, and give means for aplication to a actual experimental machine, And, we show results of the moving motions in experiments by actual machine.

We are interested in the dynamical mobility of a simple mechanism with two links and one-motor, which moves in one dimension. It can move with rotation of the lower link led by the swing of the upper link. We have developed a two-link-one-motor experimental robot, implemented a detailed simulation for this system which include backlash or shock in landing, and designed a non-linear feedback controller to realize one step stable motion of this mechanism. © 2005 IEEE.