Robotic Platform for Horticulture: Assessment Methodology and Increasing the Level of Autonomy

The relevance of the study is confirmed by the rapid development of automation in agriculture, in particular, horticulture; the lack of methodological developments to assess the effectiveness of the introduction of robotic technologies; and the need to expand the functionality of mobile robots. The purpose of the study was to increase the level of autonomy of a robotic platform for picking apple fruits based on a new method, develop a system of factors to determine the effectiveness of the introduction of robots in horticulture, and develop a control system using integrated processing of onboard data. The article discussed the efficiency factors for the introduction of robotic systems and technologies in agricultural enterprises specializing in horticulture within the framework of projects with different budgets. The study sample consisted of 30 experts-enterprises that have implemented robotic platforms and scientists specializing in this field. Based on an expert survey of enterprise specialists, a ranked list of 18 efficiency factors was obtained. To select an evaluation factor that determines the effectiveness of robotization and the developed control system, a method for calculating the concordance coefficient (method of expert analysis) was applied as a measure of the consistency of a group of experts for each group of factors. An analysis of the results of the expert evaluation showed that three factors are the most significant: the degree of autonomy of work; positioning accuracy; and recognition accuracy. The generalized indicator of local autonomy of task performance was estimated based on the analysis of a set of single indicators. A system for controlling the movement of an autonomous robotic wheeled platform based on inertial and satellite navigation and calculation of the path to be overcome was developed. The developed software allows for the design of a route for the robotic platform in apple horticulture to automatically perform various technological operations, such as fertilization, growth and disease control, and fruit harvesting. With the help of the software module, the X, Y coordinates, speed and azimuth of movement were given, and the movement of the platform along the given typical turn trajectories in an intensive horticulture environment was visualized.

Composite SOSM controller for path tracking control of agricultural tractors subject to wheel slip

In the work, the path tracking control methods are developed for autonomous agricultural tractors subject to wheel slip constraints by using second-order sliding mode (SOSM) and finite-time disturbance observer (FDOB) techniques. First of all, the path tracking error dynamics derived from the kinematic model is given and applied to controller design. In order to deal with the inevitable chattering problem existing in the conventional first-order sliding mode (FOSM) controller, a SOSM controller is constructed by regarding the controller derivative as the new control law, which means that the practical control law can be seen as an integration of the SOSM controller. Through a combination of the FDOB and the designed SOSM controller, the composite path tracking controller is further constructed to avoid high control gains in the designed SOSM controller. The strict Lyapunov stability analysis is carried out to ensure that the sliding variable can be finite-time stabilized to the origin under the proposed control algorithms. Finally, the comparative simulation results confirm that the developed guidance laws can achieve good tracking performance and strong robustness even in the presence of slipping effects.

AVALIAÇÃO DA PRECISÃO DE DIFERENTES DISPOSITIVOS GNSS

A utilização de dispositivos GNSS (Global Navigation Satellite System) para aplicação em atividades agrícolas, construção civil, aeronáutica e em automóveis vem ganhando cada vez mais destaque no cenário global. O uso desta tecnologia possibilita uma abordagem mais precisa e prática para os problemas encontrados pela humanidade. Para isso, a acurácia na medição da posição é de suma importância para uma gestão precisa das atividades. Com o intuito de comparar a precisão de diferentes tipos de receptores (GPS de Navegação em dispositivo próprio e em Smartphone e GPS topográfico), este trabalho consistiu na realização de três diferentes testes de acurácia de posicionamento (testes de altura, alinhamento e área) frente a uma medição de referência (trena), para com isso avaliar a aplicabilidade destes dispositivos em operações que demandam alta precisão. Concluiu-se que o GPS Topográfico obteve o melhor desempenho dentro os demais dispositivos nos testes. No entanto, nenhum dos receptores apresentou resultados satisfatórios para serem utilizados em operações que demandam alta precisão.

Vision-Based Mowing Boundary Detection Algorithm for an Autonomous Lawn Mower

This study proposes a vision-based mowing boundary detection algorithm for an autonomous lawn mower. An autonomous lawn mower requires high moving accuracy for efficient mowing. This problem is solved by using a vision system to detect the boundary of two regions, i.e., before and after the lawn mowing process. The mowing boundary cannot be detected directly because it is ambiguous. Therefore, we utilize a texture classification method with a bank of filters for classifying the input image of the lawn field into two regions as mentioned above. The classification is performed by threshold processing based on a chi-squared statistic. Then, the boundary line is detected from the classified regions by using Random sample consensus (RANSAC). Finally, we apply the proposed method to 12 images of the lawn field and verified that the proposed method can detect a mowing boundary line with centimeter accuracy in a dense lawn field.

Instantaneous Real-Time Kinematic Decimeter-Level Positioning with BeiDou Triple-Frequency Signals over Medium Baselines

Many applications, such as marine navigation, land vehicles location, etc., require real time precise positioning under medium or long baseline conditions. In this contribution, we develop a model of real-time kinematic decimeter-level positioning with BeiDou Navigation Satellite System (BDS) triple-frequency signals over medium distances. The ambiguities of two extra-wide-lane (EWL) combinations are fixed first, and then a wide lane (WL) combination is reformed based on the two EWL combinations for positioning. Theoretical analysis and empirical analysis is given of the ambiguity fixing rate and the positioning accuracy of the presented method. The results indicate that the ambiguity fixing rate can be up to more than 98% when using BDS medium baseline observations, which is much higher than that of dual-frequency Hatch-Melbourne-Wübbena (HMW) method. As for positioning accuracy, decimeter level accuracy can be achieved with this method, which is comparable to that of carrier-smoothed code differential positioning method. Signal interruption simulation experiment indicates that the proposed method can realize fast high-precision positioning whereas the carrier-smoothed code differential positioning method needs several hundreds of seconds for obtaining high precision results. We can conclude that a relatively high accuracy and high fixing rate can be achieved for triple-frequency WL method with single-epoch observations, displaying significant advantage comparing to traditional carrier-smoothed code differential positioning method.

A simple method to improve autonomous GPS positioning for tractors

Error is always present in the GPS guidance of a tractor along a desired trajectory. One way to reduce GPS guidance error is by improving the tractor positioning. The most commonly used ways to do this are either by employing more precise GPS receivers and differential corrections or by employing GPS together with some other local positioning systems such as electronic compasses or Inertial Navigation Systems (INS). However, both are complex and expensive solutions. In contrast, this article presents a simple and low cost method to improve tractor positioning when only a GPS receiver is used as the positioning sensor. The method is based on placing the GPS receiver ahead of the tractor, and on applying kinematic laws of tractor movement, or a geometric approximation, to obtain the midpoint position and orientation of the tractor rear axle more precisely. This precision improvement is produced by the fusion of the GPS data with tractor kinematic control laws. Our results reveal that the proposed method effectively reduces the guidance GPS error along a straight trajectory.

Steering a tractor by means of an EMG-based human-machine interface

An electromiographic (EMG)-based human-machine interface (HMI) is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI) from the Emotiv Company, was employed. This device, by means of 14 saline sensors, measures and processes EMG and electroencephalographic (EEG) signals from the scalp of the driver. In our tests, the HMI took into account only the detection of four trained muscular events on the driver's scalp: eyes looking to the right and jaw opened, eyes looking to the right and jaw closed, eyes looking to the left and jaw opened, and eyes looking to the left and jaw closed. The EMG-based HMI guidance was compared with manual guidance and with autonomous GPS guidance. A driver tested these three guidance systems along three different trajectories: a straight line, a step, and a circumference. The accuracy of the EMG-based HMI guidance was lower than the accuracy obtained by manual guidance, which was lower in turn than the accuracy obtained by the autonomous GPS guidance; the computed standard deviations of error to the desired trajectory in the straight line were 16 cm, 9 cm, and 4 cm, respectively. Since the standard deviation between the manual guidance and the EMG-based HMI guidance differed only 7 cm, and this difference is not relevant in agricultural steering, it can be concluded that it is possible to steer a tractor by an EMG-based HMI with almost the same accuracy as with manual steering.