Advanced Non-Chemical and Close to Plant Weed Control system for Organic Agriculture

Use of chemical has been reduced in agriculture for controlling weeds emergence. The use of alternative systems, such as cultural practices (mulching, flame, intercropping etc.) and mechanical system (hoe, tine etc.) has been introduced by various researchers. Automation technique based on sensors controlled system has enhanced the efficiency of the mechanical system for weed control. Mostly, low cost image acquisition sensors and optical sensor to detect the plant ensuring swift operation of vehicles close the crop plants to remove competitive weeds. The available system need to be evaluated to get best possible system for close to plant (CTP) weed removal. In the study various non-chemical weed control measures has been explored and 30 mechanical tools for CTP were evaluated. High precision tillage solutions and thermal weed control by pulsed lasers for eradication of stem or main shoot were found to be the most promising weed control concepts for CTP operation

Automation and the farmer

A current problem in Australia is the shortage of human assistance for farmers. Automation and technological innovation are discussed as answers to this, delegating tasks to ‘robot’ systems. By way of example, projects are examined that have been conducted over the years at the NCEA, including vision guidance of tractors, quality assessment of produce, discrimination between plants and weeds and determination of cattle condition using machine vision. Strategies are explored for extending the current trends that use machine intelligence to reduce the need for human intervention, including the concept of smaller but more intelligent autonomous devices. Concepts of teleoperation are also explored, in which assistance can be provided by operatives remote from the process. With present advances in communication bandwidth, techniques that are common for monitoring remote trough water levels can be extended to perform real-time dynamic control tasks that range from selective picking to stock drafting

Hortibot: Feasibility study of a plant nursing robot performing weeding operations – part IV

Based on the development of a robotic tool carrier (Hortibot) equipped with weeding tools, a feasibility study was carried out to evaluate the viability of this innovative technology. The feasibility was demonstrated through a targeted evaluation adapted to the obtainable knowledge on the system performance in horticulture. A usage scenario was designed to set the implementation of the robotic system in a row crop of seeded bulb onions considering operational and functional constraints in organic crop, production. This usage scenario together with the technical specifications of the implemented system provided the basis for the feasibility analysis, including a comparison with a conventional weeding system. Preliminary results show that the automation of the weeding tasks within a row crop has the potential of significantly reducing the costs and still fulfill the operational requirements set forth. The potential benefits in terms of operational capabilities and economic viability have been quantified. Profitability gains ranging from 20 to 50% are achievable through targeted applications. In general, the analyses demonstrate the operational and economic feasibility of using small automated vehicles and targeted tools in specialized production settings

Autonomous Inter-Row Hoeing using GPS-based side-shift control

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 9 (2007): Autonomous Inter-Row Hoeing using GPS-based side-shift control. Manuscript ATOE 07 005. Vol. IX. July, 2007

Development of a camera-vision guided automatic sprayer

This study describes the design and development of a camera-vision guided unmanned mover sprayer for the purpose of automatic weed control. The sprayer system was mounted on the mover. Modifications were carried out for both sprayer and mover systems, so that it can be operated remotely. The automated system was developed using the electromechanical system and controllers. It is capable of directing the mover sprayer to the target location given by the user. The electromechanical system was developed to control the ignition, the accelerator and the spraying systems. The controllers consist of an I/O module (ICPCON I-87057) and also a pair of radio modems (SST-2400) for data transmission. The graphical user interface (GUI) software to control the automatic system was developed by using Visual Basic Programming. The GUI has features which enable the user to perform desired tasks using the computer instead of going directly to the sprayer/mover. The combination of the multi controllers and developed control software in the development of the camera-vision-guided unmanned mover sprayer can reduce drudgery and increase safety

Automatic guidance system for farm tractor

Use of the conservation tillage system known as ridge-till has steadily increased for corn and soybean production. It is important to plant rows at the same location and to rebuild the ridges in the same location every year. Without a system to guide along the previous ridge, guess rows become wide in places and narrow in others. This causes plants to be damaged during cultivation and yield to be lost during harvest;An automatic guidance system based upon two position-sensing systems was designed to follow a desired path. The position sensing system generates and transmits radio signals to a pair of repeaters through a main antenna. Returned signals from repeaters are used to determine the tractor position in the field. A microcomputer calculated the lateral position error, determined the proper steering angle, and controlled a stepping motor to steer the tractor. The lateral position error was determined by comparing the present measured position with the desired tractor position. A control algorithm was developed based upon the kinematic behavior of the tractor. The control algorithm determined the steering angle which would reduce the lateral position error. The position error of the front wheel at the looking-ahead next measurement position, the current front wheel angle, and the angle difference between the tractor yaw and the slope of curvature of the desired path were used to determine the steering angle;The steering control algorithm was evaluated for different front wheel turning ratios and sampling distance intervals through use of computer simulation. Experiments were conducted to verify the algorithm under field conditions. A John Deere 4430 tractor was equipped with the automatic guidance system. Paths considered for the field experiments were a 70-m straight line path, a sinusoidal path with a 5-m amplitude and 50-m period, and a 5-m step path. Position error at the tractor front wheel and at a three-point-hitch mounted implement was analyzed. Maximum absolute error, RMS (Root Mean Squared) error, and percentage of measured points where the absolute error was greater than 50 cm were calculated. Results showed that acceptable precision for field operations requires a guidance system with a position-measurement error of less than 5 cm. More accurate position and tractor yaw angle measurement, and faster error processing are required to improve the field performance of the guidance system

Mapping Wide Row Crops with Video Sequences Acquired from a Tractor Moving at Treatment Speed

This paper presents a mapping method for wide row crop fields. The resulting map shows the crop rows and weeds present in the inter-row spacing. Because field videos are acquired with a camera mounted on top of an agricultural vehicle, a method for image sequence stabilization was needed and consequently designed and developed. The proposed stabilization method uses the centers of some crop rows in the image sequence as features to be tracked, which compensates for the lateral movement (sway) of the camera and leaves the pitch unchanged. A region of interest is selected using the tracked features, and an inverse perspective technique transforms the selected region into a bird’s-eye view that is centered on the image and that enables map generation. The algorithm developed has been tested on several video sequences of different fields recorded at different times and under different lighting conditions, with good initial results. Indeed, lateral displacements of up to 66% of the inter-row spacing were suppressed through the stabilization process, and crop rows in the resulting maps appear straight

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

Vision-based weed identification with farm robots

Robots in agriculture offer new opportunities for real time weed identification and quick removal operations. Weed identification and control remains one of the most challenging task in agriculture, particularly in organic agriculture practices. Considering environmental impacts and food quality, the excess use of chemicals in agriculture for controlling weeds and diseases is decreasing. The cost of herbercides and their field applications must be optimized. As an alternative, a smart weed identification technique followed by the mechanical and thermal weed control can fulfill the organic farmers’ expectations. The smart identification technique works on the concept of ‘shape matching’ and ‘active shape modeling’ of plant and weed leafs. The automated weed detection and control system consists of three major tools. Such as: i) eXcite multispectral camera, ii) LTI image processing library and iii) Hortibot robotic vehicle. The components are combined in Linux interface environment in the eXcite camera associate PC. The laboratory experiments for active shape matching have shown interesting results which will be further enhanced to develop the automated weed detection system. The Hortibot robot will be mounted with the camera unit in the front-end and the mechanical weed remover in the rear-end. The system will be upgraded for intense commercial applications in maize and other row crops