GPS-guided mobile robot platform featuring modular design elements for agricultural applications : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University Turitea Campus, Palmerston North, New Zealand

The agricultural industry has not seen significant innovation in development of low-cost automated farming solutions, with current systems costing several thousands of dollars to implement. Currently these automated solutions are primarily implemented around crop planting and harvesting, and the large implementation cost of these systems makes them unfeasible for small-scale operations. Within many agricultural industries, workers expend a considerable amount of time undertaking simple tasks that are labour intensive. Many of these tasks could instead be completed using a self-driving robotic platform outfitted with the appropriate devices required for the tasks. This thesis covers the research work aiming to produce a solution that could turn an existing farming vehicle into a multipurpose low-cost agricultural platform, to act as the platform for an autonomous vehicle capable of performing pre-programmed tasks within an agricultural environment. A quad bike was selected as the vehicle platform for this research in which the control modules would control the speed and direction of this farm bike. Four modules were developed to control the vehicle components that would normally be operated by a human operator. These modules are comprised of mechanical actuators coupled with a microcontroller control system and includes some specific designs to maintain the user's ability to manually control the pre-existing systems. A gear-changing module controls the vehicles manual gearbox, providing a method to detect and control the vehicles current gear. A speed control module was developed to control the vehicles throttle and braking system and detects the vehicles speed. A steering module controls the vehicles steering system, allowing for accurate control of the vehicles direction. Finally, a vehicle controller module provides a central command interface that ties the previous three modules together and controls the vehicles electrical components and engine. Development of a low-cost differential GPS (DGPS) system was also undertaken to reduce the implementation cost of the system. Due to inconclusive results in relation to the positional accuracy of this system is was decided that a standard GPS system would be used for the vehicle prototype with further development on the DGPS system would be undertaken in future development of the research. The successful development of a farm automated vehicle platform was achieved through this research. With further improvement on software, intelligent control and the development of a low-cost differential global positioning satellite (GPS) system, a fully autonomous farm platform that can be outfitted with different tools or devices for the required farm tasks is feasible and practical

Proceedings of the 4th field robot event 2006, Stuttgart/Hohenheim, Germany, 23-24th June 2006

Zeer uitgebreid verslag van het 4e Fieldrobotevent, dat gehouden werd op 23 en 24 juni 2006 in Stuttgart/Hohenhei

Index to 1981 NASA Tech Briefs, volume 6, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1981 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

Fully-autonomous miniaturized robots (e.g., drones), with artificial intelligence (AI) based visual navigation capabilities are extremely challenging drivers of Internet-of-Things edge intelligence capabilities. Visual navigation based on AI approaches, such as deep neural networks (DNNs) are becoming pervasive for standard-size drones, but are considered out of reach for nanodrones with size of a few cm${}^\mathrm{2}$. In this work, we present the first (to the best of our knowledge) demonstration of a navigation engine for autonomous nano-drones capable of closed-loop end-to-end DNN-based visual navigation. To achieve this goal we developed a complete methodology for parallel execution of complex DNNs directly on-bard of resource-constrained milliwatt-scale nodes. Our system is based on GAP8, a novel parallel ultra-low-power computing platform, and a 27 g commercial, open-source CrazyFlie 2.0 nano-quadrotor. As part of our general methodology we discuss the software mapping techniques that enable the state-of-the-art deep convolutional neural network presented in [1] to be fully executed on-board within a strict 6 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 64 mW on average. Our navigation engine is flexible and can be used to span a wide performance range: at its peak performance corner it achieves 18 fps while still consuming on average just 3.5% of the power envelope of the deployed nano-aircraft.Comment: 15 pages, 13 figures, 5 tables, 2 listings, accepted for publication in the IEEE Internet of Things Journal (IEEE IOTJ

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio