Tomoo Shiigi

Moving Object Localization Using Sound-Based Positioning System with Doppler Shift Compensation

Sound-based positioning systems are a potential alternative low-cost navigation system. Recently, we developed such an audible sound-based positioning system, based on a spread spectrum approach. It was shown to accurately localize a stationary object. Here, we extend this localization to a moving object by compensating for the Doppler shift associated with the object movement. Numerical simulations and experiments indicate that by compensating for the Doppler shift, the system can accurately determine the position of an object moving along a non-linear path. When the object moved in a circular path with an angular velocity of 0 to 1.3 rad/s, it could be localized to within 25 mm of the actual position. Experiments also showed the proposed system has a high noise tolerance of up to −25 dB signal-to-noise ratio (SNR) without compromising accuracy.

Development of a Mobile Grading Machine for Citrus Fruit

A mobile grading machine for citrus fruits has been developed to collect crop information such as fruit yield, diameter, and sugar content of fruits of each tree part. It consists of a mobile mechanism, a differential global positioning system, a fruit conveyer system, a color camera for machine vision, a NIR spectrometer, and a personal computer for control and database. Preliminary field tests were conducted to investigate basic performance of this machine in a mandarin orange orchard. Using the collecting data of fruit yield and diameter and sugar content of fruit, crop information maps of each tree part was made. These maps indicated that each tree part has large variability of yield, size, and sugar content of fruit.

Development of an End-Effector for a Tomato Cluster Harvesting Robot

Abstract An end-effector was developed for a tomato cluster harvesting robot. This end-effector can harvest not individual fruits but a whole fruit cluster to improve the robots harvest efficiency. Experiments for harvesting tomato clusters were conducted in a high-density plant training system. According to a harvesting algorithm, the end-effector was able to perform well, even when target peduncle orientations were not given. Although the success rate of harvesting tomato clusters was 50 %, it is considered that this rate would improve if an end-effector is used for the high-wire tomato plant training systems in Dutch systems where the node lengths of plants are long enough to loosely hold the main stems.

Investigation of Excitation Wavelength for Fluorescence Emission of Citrus Peels based on UV-VIS Spectra

A study was conducted to investigate the best wavelengths for fluorescence excitation and the resulting fluorescence wavelengths in the range of 300-700 nm with citrus peels taken from 15 varieties, which are concerned with detection of surface defects of citrus fruits. Characteristics of UV absorbance, excitation and fluorescence spectra were observed by variety, and principle components analysis (PCA) and discriminate analysis (DA) were used to categorize the citrus varieties by fluorescence intensity levels in order to give some tips for optimizing the fluorescence imaging based machine vision system. The observed proper excitation wavelength for best fluorescence emmision and resulting peak fluorescence wavelength varied variety to variety and ranged from 350 to 380 nm and 490 to 540 nm respectively. The selected varieties of citrus were categorized successfully into four groups of known fluorescence level, namely strong, medium, weak and no fluorescence groups.

A Machine Vision System for Tomato Cluster Harvesting Robot

Abstract Dutch style greenhouse for tomato production has become popular recently in many countries while cluster tomatoes have gained popularity among consumers.. To improve harvest efficiency of the cluster tomatoes in large scale Dutch production systems, it is desirable to replace manual labor with automated machines. In this paper, a machine vision system developed for autonomous tomato fruit cluster harvesting is described. Since the difficulty of recognizing the grasping point depended on exposure of plant parts and on robot access angle, acquired images were classified into three groups. The research results show a 73% success rate in automatically locating grasping points for the robotic end-effector on main stems of the cluster tomatoes that can be visually identified by human eyes.

Identification of UV-Fluorescence Components for Detecting Peel Defects of Lemon and Yuzu using Machine Vision

Abstract Fluorescence imaging has been used to detect peel defects in many citrus varieties, but not in lemon and yuzu. In this study, we extract and identify fluorescent components from the peel of lemon and yuzu. The characteristics of excitation and fluorescence of these extracted components were determined, and their identity clarified using NMR spectroscopy. Extracted fluorescent components for both lemon and yuzu have a coumarin structure. Two coumarins (5-7-dimethoxycoumarin,5-geranyloxy-7-methoxycoumarin) were identified in lemon and one (5-geranyloxycoumarin) in yuzu. Their excitation and fluorescence wavelength were observed at 320–330 nm and 380–400 nm, respectively. Moreover, when a fluorescence imaging system was set-up with UV-A illumination, it was shown that this systemcan detect peel defects in lemon, and to a lesser extent in yuzu.

Position Detecting Method Using Spread Spectrum Sound-Correction Method of Measurement Error by Compensating Wind and Temperature-

Abstract GPS has become a common technology for a positioning system of vehicles outdoor. In agriculture, the RTK-GPS has been used for autonomous tractors and harvesters in researches, and their measurement accuracy was sufficient. In room, however, the GPS measurement errors were larger because of delayed or covered electric waves. Rail or electromagnetic induction type position sensing methods have been used for autonomous mobile robots under greenhouses or other facilities. There are problems that installation costs are expensive and route modification is not easy, when those systems are used in agricultural facilities. In this research, a positioning system using spread spectrum sound is described and noise tolerance and signal identification could be improved by using a spread spectrum technique. So far, a system for measuring distance was developed and estimation of measurement accuracy was conducted. As a result of measurement distance 10m between microphone and speaker under non wind and non temperature gradient, RMSE 3.4mm was obtained. It is also known, however, the measurement error increases under windy and changeable temperature conditions. In this research, a correction method of the measurement error by wind and temperature is developed and estimated.

Accurate Position Detecting during Asparagus Spear Harvesting using a Laser Sensor

A serious problem in Japanese agriculture is the aging and shortage of farm laborers. Agricultural robots are expected to solve or alleviate this problem, as well as provide additional information about agricultural products. In this research, we focus on machine vision for an asparagus harvesting robot. Although TV cameras are often used for machine vision in harvesting robots, it is difficult to use them in direct sunlight, due to fluctuations in illumination intensity and color temperature effects of sunlight. So a laser sensor was used. This sensor detected asparagus spears based on their distance from sensor and their length. Total success rate of detection was 75 % of asparagus spears and 71 % of parent asparagus.

Machine Vision System for Detecting Fluorescent Area of Citrus Using Fluorescence Image

Abstract This research is carried out to develop a machine vision system which could identify the fluorescence area on injured or defective citrus surfaces. The target objects whose surfaces were injured by needle insertions were acquired by a camera VGA using UV lamps (radiating Blacklight and UV-B wave-lengths) and white LEDs. Because damaged citrus peel includes fluorescent substances, it was easy to discriminate fluorescence parts from healthy parts. The results showed that the blacklighting system is practical and feasible, and that the proposed algorithm of fluorescence area detection is effective for some varieties of citrus.

Sound-Based ranging system in greenhouse environment with multipath effect compensation using artificial neural network

In this study, sound-based ranging system in greenhouse environment with compensation of measurement error caused by multipath effect using Artificial Neural Network (ANN) was proposed. Greenhouse environment has special characteristic which is different with condition where the similar system that previously developed were applied. There are challenges need to be handled in developing accurate ranging system in greenhouse such as high humidity, temperature gradient, wind, and obstacles. In this study, error compensation was performed by first estimating the measurement error using some features extracted from the cross-correlation wave of the received signal by using ANN. Then, the estimated value was used to compensate the measurement error. The experiment result showed the feasibility to apply the proposed method to improve accuracy of sound-based ranging system in greenhouse environment.