Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

Bringing the farmer perspective to agricultural robots

The research reported in this paper explores autonomous technologies for agricultural farming application and is focused on the development of multiple-cooperative agricultural robots (AgBots). These are highly autonomous, small, lightweight, and unmanned machines that operate cooperatively (as opposed to a traditional single heavy machine) and are suited to work on broadacre land (large-scale crop operations on land parcels greater than 4,000m2). Since this is a new, and potentially disruptive technology, little is yet known about farmer attitudes towards robots, how robots might be incorporated into current farming practice, and how best to marry the capability of the robot with the work of the farmer. This paper reports preliminary insights (with a focus on farmer-robot control) gathered from field visits and contextual interviews with farmers, and contributes knowledge that will enable further work toward the design and application of agricultural robotics.

Design of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture

This thesis presents the design process and the prototyping of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture. Achieved by the joint operation of multiple autonomous vehicles to improve energy consumption, reduce labour, and increase efficiency in the application of inputs for the management of crops. The Small Robotic Farm Vehicle (SRFV) is a lightweight and energy efficient robotic vehicle with a configurable, modular design. It is capable of undertaking a range of agricultural tasks, including fertilising and weed management through mechanical intervention and precision spraying, whilst being more than an order of magnitude lower in weight than existing broadacre agricultural equipment.

Field and Service Robotics Results of the 5th International Conference

The 5th International Conference on Field and Service Robotics (FSR05) was held in Port Douglas, Australia, on 29th - 31st July 2005, and brought together the worlds' leading experts in field and service automation. The goal of the conference was to report and encourage the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience. Field robots are robots which operate in outdoor, complex, and dynamic environments. Service robots are those that work closely with humans, with particular applications involving indoor and structured environments. There are a wide range of topics presented in this issue on field and service robots including: Agricultural and Forestry Robotics, Mining and Exploration Robots, Robots for Construction, Security & Defence Robots, Cleaning Robots, Autonomous Underwater Vehicles and Autonomous Flying Robots. This meeting was the fifth in the series and brings FSR back to Australia where it was first held. FSR has been held every 2 years, starting with Canberra 1997, followed by Pittsburgh 1999, Helsinki 2001 and Lake Yamanaka 2003.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

Networked control system for the guidance of a four-wheel steering agricultural robotic platform

A current trend in the agricultural area is the development of mobile robots and autonomous vehicles for precision agriculture (PA). One of the major challenges in the design of these robots is the development of the electronic architecture for the control of the devices. In a joint project among research institutions and a private company in Brazil a multifunctional robotic platform for information acquisition in PA is being designed. This platform has as main characteristics four-wheel propulsion and independent steering, adjustable width, span of 1,80m in height, diesel engine, hydraulic system, and a CAN-based networked control system (NCS). This paper presents a NCS solution for the platform guidance by the four-wheel hydraulic steering distributed control. The control strategy, centered on the robot manipulators control theory, is based on the difference between the desired and actual position and considering the angular speed of the wheels. The results demonstrate that the NCS was simple and efficient, providing suitable steering performance for the platform guidance. Even though the simplicity of the NCS solution developed, it also overcame some verified control challenges in the robot guidance system design such as the hydraulic system delay, nonlinearities in the steering actuators, and inertia in the steering system due the friction of different terrains. Copyright © 2012 Eduardo Pacincia Godoy et al.

Non invasive moisture measurement in agricultural fiel using a rolling spherical robot

Irrigation management in large crop fields is a very important practice. Since the farm management costs and the crop results are directly connected with the environmental moisture, water control optimization is a critical factor for agricultural practices, as well as for the planet sustainability. Usually, the crop humidity is measured through the water stress index (WSI), using imagery acquired from satellites or airplanes. Nevertheless, these tools have a significant cost, lack from availability, and dependability from the weather. Other alternative is to recover to ground tools, such as ground vehicles and even static base stations. However, they have an outstanding impact in the farming process, since they can damage the cultivation and require more human effort. As a possible solution to these issues, a rolling ground robot have been designed and developed, enabling non-invasive measurements within crop fields. This paper addresses the spherical robot system applied to intra-crop moisture measurements. Furthermore, some experiments were carried out in an early stage corn field in order to build a geo-referenced WSI map.

Risk analysis for UAV safe operations: a rationalization for an agricultural environment

The road to the automation of the agricultural processes passes through the safe operation of the autonomous vehicles. This requirement is a fact in ground mobile units, but it still has not well defined for the aerial robots (UAVs) mainly because the normative and legislation are quite diffuse or even inexistent. Therefore, to define a common and global policy is the challenge to tackle. This characterization has to be addressed from the field experience. Accordingly, this paper presents the work done in this direction, based on the analysis of the most common sources of hazards when using UAV's for agricultural tasks. The work, based on the ISO 31000 normative, has been carried out by applying a three-step structure that integrates the identification, assessment and reduction procedures. The present paper exposes how this method has been applied to analyze previous accidents and malfunctions during UAV operations in order to obtain real failure causes. It has allowed highlighting common risks and hazardous sources and proposing specific guards and safety measures for the agricultural context.

A Low Cost Controller Board for Teaching Robotics

This paper presents the Smarty Board; a new micro-controller board designed specifically for the robotics teaching needs of Australian schools. The primary motivation for this work was the lack of commercially available and cheap controller boards that would have all their components including interfaces on a single board. Having a single board simplifies the construction of programmable robots that can be used as platforms for teaching and learning robotics. Reducing the cost of the board as much as possible was one of the main design objectives. The target user groups for this device are the secondary and tertiary students, and hobbyists. Previous studies have shown that equipment cost is one of the major obstacles for teaching robotics in Australia. The new controller board was demonstrated at high-school seminars. In these demonstrations the new controller board was used for controlling two robots that we built. These robots are available as kits. Given the strong demand from high-school teachers, new kits will be developed for the next robotic Olympiad to be held in Australia in 2006.