An Effective Multi-Cue Positioning System for Agricultural Robotics

The self-localization capability is a crucial component for Unmanned Ground Vehicles (UGV) in farming applications. Approaches based solely on visual cues or on low-cost GPS are easily prone to fail in such scenarios. In this paper, we present a robust and accurate 3D global pose estimation framework, designed to take full advantage of heterogeneous sensory data. By modeling the pose estimation problem as a pose graph optimization, our approach simultaneously mitigates the cumulative drift introduced by motion estimation systems (wheel odometry, visual odometry, ...), and the noise introduced by raw GPS readings. Along with a suitable motion model, our system also integrates two additional types of constraints: (i) a Digital Elevation Model and (ii) a Markov Random Field assumption. We demonstrate how using these additional cues substantially reduces the error along the altitude axis and, moreover, how this benefit spreads to the other components of the state. We report exhaustive experiments combining several sensor setups, showing accuracy improvements ranging from 37% to 76% with respect to the exclusive use of a GPS sensor. We show that our approach provides accurate results even if the GPS unexpectedly changes positioning mode. The code of our system along with the acquired datasets are released with this paper.Comment: Accepted for publication in IEEE Robotics and Automation Letters, 201

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.regional 2010 Research Project Plan of the Junta de Castilla y León, (Spain), under project VA034A10-2. It was also partially supported by the 2009 ITACyL project entitled ―Realidad aumentada, Bci y correcciones RTK en red para el guiado GPS de tractores (ReAuBiGPS

Design and Development of an Autonomous System for Agricultural Tractor

This study describes the design and modification of a tractor for automatic control. The automated system developed for the unmanned tractor was for the purpose of master slave operation in the agricultural sector. In this study, an hydrostatic transmission of the Kubota tractor was selected as the research platform. Modifications were carried out in order to automate the manual control tractor. The automated system was capable to direct the tractor to the target location given by the user. The sensing system guides the tractor to move along the path determined by the controller based on the information from the sensors. The automated system was developed by combining of electromechanical system, multi-sensor integration and control software. The electromechanical system (electrohydraulic and electro-pneumatic) was used to control the gear, brake, steering and accelerator system. The integration of sensors (Ultrasonic sensor, range sensor, magnetic sensor, encoder and potentiometer) provided the surrounding information to the tractor controller. The controller consists of series I/O modules (ICP 17000) and also pair of radio modem for data transmission. The graphical user interface software to control the automated system was developed using the Visual Basic. The automated system developed for ignition, gear, brake, accelerator and steering systems can be control remotely through the use of Graphical User Interface (GUI). The GUI has features, which enable the user to monitor the tractor condition and movement of the tractor by referring to the simulation layer. The simtdation layer consist of pre-determined field map, scaled at lcm: 1m.The simulation movement of the tractor was configured to coordinate with the real tractor movement. The GUI also enables the user to use keyboard to control the tractor movement. The GUI has a capability to calculate the location of the given target location and plan the tractor movement to the target location and assist the tractor to avoid the obstacle in the tractor path

A Novel Approach to Autonomous Farming Robot

Now-a-days everyone has lost interest from farming as it has become a very difficult and tedious job. Although hi-tech vehicles and equipment have overcome older version of vehicles and equipment and also they made farming quite easy. But it still requires a plenty of human effort. Today automation has been introduced in almost every form of industry and a prominent reason to reducing human effort. Our Objective is to reduce human efforts in farming as we planned to develop an autonomous guidance system for farm vehicles. Our system will be based on Global Positioning System (GPS) [1]. To develop complete autonomous system, other than GPS, systems like machine vision, laser-based sensors, inertial sensors would be needed to be employed for avoiding obstacles in the path and overcoming other challenges. However making such systems would require more time and monetary resources then available, hence developing such complete autonomous system is out of scope of the current task at hand. Our aim is to develop a Mixture of such complete autonomous system which will fulfill one of the Basic needs of a complete autonomous guidance system. DOI: 10.17762/ijritcc2321-8169.160412

GNSS in Precision Agricultural Operations

Today, there are two Global Navigation Satellite Systems (GNSS) that are fully operational and commercially available to provide all-weather guidance virtually 24 h a day anywhere on the surface of the earth. GNSS are the collection of localization systems that use satellites to know the location of a user receiver in a global (Earth-centered) coordinate system and this has become the positioning system of choice for precision agriculture technologies. At present North American Positioning System known as Navigation by Satellite Timing and Ranging Global Position System (NAVSTAR GPS or simply GPS) and Russian Positioning System known as Globalnaya Navigatsionnaya Sputnikovaya Sistema or Global Navigation Satellite System (GLONASS) both qualify as GNSS. Two other satellite localization systems, Galileo (European Union) and Compass (Chinese), are expected to achieve full global coverage capability by 2020. Detailed information on GNSS technology is plentiful, and there are many books that provide a complete description of these navigation systems [9- 11]. But the focus of this chapter is on the applications of GPS in agricultural operations. These applications include positioning of operating machines, soil sampling, variable rate application and vehicle guidance.Comisión Europea FP7/2007-201

Comparison of positional accuracy between RTK and RTX GNSS gased on the autonomous agricultural vehicles under field conditions

Currently, many systems (machine vision, high resolution remote sensing, global positioning systems, and odometry techniques) have been integrated into agricultural e quipment to increase the efficiency, productivity, and safety of the individual in all field activities. This study focused upon assessing a satellite-based localization solution used in straight path guidance of an autonomou s vehicle developed for ag ricultural applica tions. The autonom ous agricultural vehicle was designed and constructed under RHEA (Robot fleets for highly effective agriculture and forestry management) project and is part of a three-unit fleet of similar vehicles. Static tests showed that 99% of all positions are placed within a circle with a 2.9 cm radius centered at the geo-position usi ng real-time satellite corrections (RTX). Dynamic tests between rows demonstrated a mean (N=610) of the standard deviation for real-time base station corrections (RTK) of 1.43 cm and for real-time satellite corrections (RTX) of 2.55 cm. These re sults demonstrate that the tractor was able to track each straight line with high degree of accuracy. The integration of a Global Navigation Satellite System (GNSS) with sensors (e.g., inertial sensor, altimeters, odomet ers, etc.) within the vehicle showed th e potential of autonomous tractors for expanding agricultural applications utilizing this technology.European Union FP7/2007-201

Intelligent Behavior of Autonomous Vehicles in Outdoor Environment

The objective of this PhD-project has been to develop and enhance the operational behaviour of autonomous or automated conventional machines under out-door conditions. This has included developing high-level planning measures for the maximisation of machine productivity as an important element in the continued efforts of planning and controlling resource inputs in both arable and high value crops farming. The methods developed generate the optimized coverage path for any field regardless of its complexity on 2D or 3D terrains without any human intervention and in a manner that minimizes operational time, skipped and overlapped areas, and fuel consumption. By applying the developed approaches, a reduction of more than 20% in consumed fossil fuel together with a corresponding reduction in the emissions of CO2 and other greenhouses is achievable.In this work, a software package for the autonomous navigation of field robotics over 2D and 3D field terrains and the optimization of field operations and machinery systems have been developed. A web-based version of the developed software package is currently under progress

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

Self-tuning controller for farm tractor guidance

A global position-sensing system using navigational technology has been researched and applied to control a farm tractor in field conditions. Besides guiding a tractor in conservation tillage systems, navigational positioning systems can be used to generate field maps which can help in the application of chemicals and in visualizing variation of soil and crop conditions;A tractor dynamic simulator was developed by using a semi-recursive formulation which uses the variational vector approach and relative coordinates in Cartesian space. Typical joints were formulated for automatic assembly of equations of motion, and cut-joint Jacobians were used to handle with a closed-loop mechanism;A self-tuning steering controller, which can be used for all non-contact types of the positioning systems, was designed for tractor guidance systems. A simple two degrees-of-freedom model of a tractor was chosen to develop a prediction model used in recursive least-squares parameter estimation. A variable forgetting factor was implemented, and its algorithm was modified to cope with time-varying nonlinear systems. The self-tuning steering controller based upon minimum variance control was tested and verified by using the tractor dynamic simulator. Test paths used were a circular path with a radius of 36 m and a composite path which consisted of two lane-change and continuous sinusoidal maneuvers. The test speeds considered were in the range of 0-18 km/h;The study found: (1) an accurate position-sensing system is the most important factor to control the tractor path within ±5 cm of the desired path; (2) a fast sampling can be achieved in practical applications because the execution time of the controller program was about 5 msec; (3) the self-tuning controller that can be used to guide a tractor with any non-contact types of positioning system can measure the position or the position error with respect to the desired path; (4) with the sampling interval 0.1 and 0.2 seconds, the controller could control the tractor position within ±5 cm of the desired path at all test speeds. (Abstract shortened with permission of author.

Development of an inexpensive guidance system for agricultural purposes

Robotics is a rapidly growing technology and robots have pervaded into most of the industries. Robotics and automation are designed to remove the human factor from the labor intensive and monotonous work and thereby decrease the associated costs. The application of robotics to agriculture is fairly recent. Robotic applications in agriculture vary from autonomous row-guidance tractors to fruit picking robots. Similarly, soil testing and soil sampling is one area in agriculture where automation of tasks and the employment of an autonomous robot would be of great use to consultants and farmers employing site specific farming techniques. Soil testing is an important part of farming used to determine the average nutrient status in a field and to obtain a measure of nutrient availability in the field. Fertilizers and other nutrients are applied to the fields based on different soil tests. Site specific farming is greatly dependent on soil testing and can result in increased yield, reduced cost and reduced water pollution. Soil testing requires a lot of soil samples and soil sampling is a time consuming, laborious process and expensive process. Most of the consultants employing site specific techniques use ATVs to get around large fields when sampling. The development of an autonomous guidance system for an ATV to perform soil sampling would be greatly beneficial to them. Labor costs would be significantly reduced and the operators would be subjected to fewer environmental elements. The use of ATVs ensures that no extra capital is needed to buy a vehicle. The use of a small vehicle like an ATV also causes less soil compaction. A WAAS enabled Differential GPS with accuracies to within 9.84 feet was used as the position sensor. Pocket PCs are more portable than a laptop computer and are more suitable for farm conditions. Shape files were used to provide the sampling points as input to the guidance program. A guidance program was made to operate on a PDA and provide guidance instructions. A microprocessor was programmed to read the guidance instructions and actuate the different components like throttle and steering. Tests were conducted to test the accuracy and consistency of the system. The offsets of each stop point from the test point were documented and analyzed. The results indicated that the system was as accurate as the GPS used for guidance. They also indicated that a guidance system can be realized with the use of very few components and an accuracy needed for soil sampling can be achieved. Avoidance routines for obstacles within the field were indicated as future developments