Intelligent Behavior of Autonomous Vehicles In Outdoor Environment (original) (raw)
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Journal of Intelligent & Robotic Systems, 2013
Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage pattern for a given 2D field has been investigated and reported. However, a great proportion of farms have rolling terrains, which have a considerable influence on the design of coverage paths. Coverage path planning in 3D space has a great potential to further optimize field operations and provide more precise navigation. Supplementary to that, energy consumption models were invoked taking into account terrain inclinations in order to provide the optimal driving direction for traversing the parallel field-work tracks and the optimal sequence for handling these tracks under the criterion of minimizing direct energy requirements. The reduced energy requirements and consequently the reduced emissions of atmospheric pollutants, e.g. CO 2 and NO, are of major concern due to their
International Journal of Advanced Robotic Systems
Technological advances combined with the demand of cost efficiency and environmental considerations has led farmers to review their practices towards the adoption of new managerial approaches, including enhanced automation. The application of field robots is one of the most promising advances among automation technologies. Since the primary goal of an agricultural vehicle is the complete coverage of the cropped area within a field, an essential prerequisite is the capability of the mobile unit to cover the whole field area autonomously. In this paper, the main objective is to develop an approach for coverage planning for agricultural operations involving the presence of obstacle areas within the field area. The developed approach involves a series of stages including the generation of field-work tracks in the field polygon, the clustering of the tracks into blocks taking into account the in-field obstacle areas, the headland paths generation for the field and each obstacle area, the implementation of a genetic algorithm to optimize the sequence that the field robot vehicle will follow to visit the blocks and an algorithmic generation of the task sequences derived from the farmer practices. This approach has proven that it is possible to capture the practices of farmers and embed these practices in an algorithmic description providing a complete field area coverage plan in a form prepared for execution by the navigation system of a field robot.
Robotics for Sustainable Broad-Acre Agriculture
Springer Tracts in Advanced Robotics, 2015
This paper describes the development of small low-cost cooperative robots for sustainable broad-acre agriculture to increase broad-acre crop production and reduce environmental impact. The current focus of the project is to use robotics to deal with resistant weeds, a critical problem for Australian farmers. To keep the overall system affordable our robot uses low-cost cameras and positioning sensors to perform a large scale coverage task while also avoiding obstacles. A multi-robot coordinator assigns parts of a given field to individual robots. The paper describes the modification of an electric vehicle for autonomy and experimental results from one real robot and twelve simulated robots working in coordination for approximately two hours on a 55 hectare field in Emerald Australia. Over this time the real robot 'sprayed' 6 hectares missing 2.6% and overlapping 9.7% within its assigned field partition, and successfully avoided three obstacles.
IJERT-Energy Efficient Autonomous Field Vehicle for Complete Coverage
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/energy-efficient-autonomous-field-vehicle-for-complete-coverage https://www.ijert.org/research/energy-efficient-autonomous-field-vehicle-for-complete-coverage-IJERTV3IS10459.pdf Nowadays, service vehicles are being implemented for various functionalities such as tour guidance vehicles [1] & vehicles for search and rescue, vacuum cleaners [3], tractors, automotive painting etc. To make these vehicles autonomous, the amount of human control and interference is to be reduced significantly. Normally, the cost of agricultural materials and systems cannot be controlled; however it should be taken into consideration during the system design. Power consumption is also another major factor to be taken into account. This paper presents a system model that aims to reduce the power consumption of the farming vehicle and to implement complete coverage of agricultural field. This type of system would gain scope for huge precision farming applications such as harvesting, seeding, spraying, applying fertilizers, tillage, and the like.
Automatic Guided Vehicles in Agricultural and Green Space Fields
Working on new equipments to increase agricultural productivity and safety, reducing human action hardness , Cemagref and Lasmea have developed an help guidance system for agricultural vehicles. The aim of this system is to help the operator to guide the machine in order to give more attention to the order task. To r each this goal, we use a visual perception of the environment because this sensor gives a solution well adapted to lots of situations. This project began with researches on a visual guidance system for a lawn mower in 1990 and has been adaptated to the development of the same system for a combine harvester in 1995. We model the lawn mower with a virtual axle, use trajectory generation to guide it, and localize the vehicle at each iteration to insure the servoing task. For the combine harvester, we decide to use the task function approach 23] and then to control the combine harvester directly in the sensor space.
Sustainability
In this study, a comprehensive overview of the available autonomous ground platforms developed by universities and research groups that were specifically designed to handle agricultural tasks was performed. As cost reduction and safety improvements are two of the most critical aspects for farmers, the development of autonomous vehicles can be of major interest, especially for those applications that are lacking in terms of mechanization improvements. This review aimed to provide a literature evaluation of present and historical research contributions toward designing and prototyping agricultural ground unmanned vehicles. The review was motivated by the intent to disseminate to the scientific community the main features of the autonomous tractor named BOPS-1960, which was conceived in the 1960s at the Alma Mater Studiorum University of Bologna (UNIBO). Jointly, the main characteristics of the modern DEDALO unmanned ground vehicle (UGV) for orchard and vineyard operations that was des...
Navigational Path-Planning For All-Terrain Autonomous Agricultural Robot
ArXiv, 2021
The shortage of workforce and increasing cost of maintenance has forced many farm industrialists to shift towards automated and mechanized approach. The key component for autonomous systems is the path planning techniques used. Coverage path planning (CPP) algorithm is used for navigating over farmlands to perform various agricultural operations such as seeding, ploughing, or spraying pesticides and fertilizers. This report paper compares novel algorithms for autonomous navigation of farmlands. For reduction of navigational constraints, a high-resolution grid map representation is taken into consideration specific to Indian environments. The free space is covered by distinguishing the grid cells as covered, unexplored, partially explored and presence of obstacle. The performance of the compared algorithms is evaluated with metrics such as time efficiency, space efficiency, accuracy, and robustness to changes in the environment. Robotic Operating System (ROS), Dassault Systemes Exper...
Field Tests of an Autonomous Field Robot for Wide-Row Cultivation
2018
In Industrial Institute of Agriculture Engineering (Poznan, Poland), together with the Institute of Vehicle of Warsaw Technical University and firm Promar Poznan action have been taken to design autonomous field robot for sowing and cultivation of crops. Designed robot is to be autonomous device. It will automatically perform the sowing, weeding and selective spraying plant crops such as sugar beet or maize. The robot will work in various terrain and weather conditions. It will move on the dirt roads and on cultivated fields, and therefore it will have to overcome mud, sand, puddles and avoid obstacles such as ruts, bumps in the road and stones. The achievement of this objective required the development of a suitable chassis, system of autonomous control in terms of driving and realization of agronomic processes.
Robotic Tankette for Intelligent Bioenergy Agriculture: Design, Development and Field Tests
Proceedings XXII Congresso Brasileiro de Autom�tica, 2018
In recent years, the use of robots in agriculture has been increasing mainly due to the high demand of productivity, precision and efficiency, which follow the climate change effects and world population growth. Unlike conventional agriculture, sugarcane farms are usually regions with dense vegetation, gigantic areas, and subjected to extreme weather conditions, such as intense heat, moisture and rain. TIBA-Tankette for Intelligent BioEnergy Agriculture-is the first result of an R&D project which strives to develop an autonomous mobile robotic system for carrying out a number of agricultural tasks in sugarcane fields. The proposed concept consists of a semi-autonomous, low-cost, dust and waterproof tankette-type vehicle, capable of infiltrating dense vegetation in plantation tunnels and carry several sensing systems, in order to perform mapping of hard-to-access areas and collecting samples. This paper presents an overview of the robot mechanical design, the embedded electronics and software architecture, and the construction of a first prototype. Preliminary results obtained in field tests validate the proposed conceptual design and bring about several challenges and potential applications for robot autonomous navigation, as well as to build a new prototype with additional functionality.