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High levels of reliability and safety are necessary and can be achieved by novel developments within automated perception, diagnosis and decision making and fault tolerant operation. The aim is to add functionality to an existing robot prototype so that it will behave in a safe, reliable and effective manner under unmanned operation. The existing m...
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... The most difficult issue facing engineers in the development of autonomous machines is making them safe and reliable. Researchers and engineers have begun to address this problem by equipping the autonomous machine with perception and sensing technologies for obstacle detection; interrupt and error handling routines; and multi-level control architectures to optimise system behavior (Griepentrog et al. 2009;Vougioukas 2009;Ruckelshausen et al. 2009;Pitla et al. 2010a, b). It is recognized that safety is paramount to the successful commercialization and deployment of autonomous field machinery. ...
A multi-faceted whole farm planning model is developed to compare conventional and autonomous machinery for grain crop production under various benefit, farm size, suitable field day risk aversion, and grain price scenarios. Results suggest that autonomous machinery can be an economically viable alternative to conventional manned machinery if the establishment of intelligent controls is cost effective. An increase in net returns of 24% over operating with conventional machinery is found when including both input savings and a yield increase due to reduced compaction. This study also identifies the break-even investment price for intelligent controls for the safe and reliable commercialization of autonomous machinery. Results indicate that the break-even investment price is highly variable depending on the financial benefits resulting from the deployment of autonomous machinery, farm size, suitable field day risk aversion, and grain prices. The maximum break-even investment price for intelligent, autonomous controls is nearly US$500 000 for the median days suitable for fieldwork when including both input savings and a yield increase due to reduced compaction.
... In these type of applications, a superior perception is usually required, and 3-D imaging provides more information about the previously mentioned surrounding structures compared with 2-D. Automated and robotic systems could have faster acceptance by farmers if their safety aspects are well fulfilled [34]. Several reviews [35][36][37] on autonomous navigation of agricultural vehicles have been written, however, there was little focus on the 3-D vision approach. ...
Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture.
... The software has already been proved that it can control robots powered by combustion engines as well as by electric motors. Furthermore, it has been demonstrated that machine safety can be improved by Fig. 3 Overview of robot software framework MobotWare [1] adding dedicated functionality [11]. Along with MobotWare both the AMS and the Armadillo Scout can be controlled using FroboMind, which is developed at University of Southern Denmark (SDU). ...
... High levels of reliability and safety are necessary and can be achieved by novel developments within automated perception, diagnosis and decision making and fault tolerant operation. To achieve these aims extra functionality has to be added so that the machine will behave in a safe, reliable and effective manner under unmanned operation [11]. The machine system and the operation conditions were assessed by a machine safety consultant to check the compliance of existing legal requirements. ...
... The machine system and the operation conditions were assessed by a machine safety consultant to check the compliance of existing legal requirements. Based on legal safety consultancy and a failure modes and effects analysis a redesign of the machine system was completed [11]. The machine will be operating unmanned but not unattended. ...
In: Special - AI in Agriculture
Today research within agricultural technology focuses beside productivity and operation costs mainly on increasing the resource efficiency of crop production. Autonomous machines have the potential to significantly contribute to this by utilizing more multi-factorial real-time sensing and embedding artificial intelligence. A multilayer controller has successfully been implemented on two outdoor machines with various implements to conduct several agricultural applications in autonomous mode. Future work has to be conducted to achieve a more integrated and flexible implement control.
... Even for the fully autonomous systems, there will still be a considerable share of human interactions needed e.g. for moving the machine to the field and adjusting and supporting it for the operation. An easy step into autonomous mode is often described as using semi-autonomous machines such as tractor formations consisting of more than one machine but controlled and supervised by a manned machine (Griepentrog et al, 2009). After that, autonomous machines could be based on deterministic and reactive autonomy. ...
Today especially in Europe operational efficiency of machines is an important product development goal because further capacity increases by size seem to be limited. Efficient semi-autonomous or autonomous machine operations are to be the next step in automation strategy in agriculture. The aim of this paper is to present descriptive results of survey responses that explore the perception of future advanced mechanization systems by German farmers including the likely adoption of automated farming machinery. In general the farmers emphasize their high interest in advanced future techniques. This is confirmed already by their investment in fully automatic guidance systems. However, farmers are still skeptical about the use of autonomous machines on their farms in terms of reliability and safety.
... Even for the fully autonomous systems, there will still be a considerable share of human interactions needed, e.g. for moving the machine to the field and adjusting and supporting it for the operation. An easy step into autonomous mode is often described as using semi-autonomous machines such as tractor formations consisting of more than one machine but controlled and supervised by a manned machine (Griepentrog et al., 2009). After that, autonomous machines could be based on deterministic and reactive autonomy. ...
In field plot experiments, the absence of correlation between error terms cannot be assumed a priori because of the continuous spatial variability of soil fertility, thus observations from adjacent plots may be biased by neighboring effects. We discuss the problem of modelling spatial variability in factorial field experiments and efficiency of using geostatistical methods in comparison with the classical, statistical approach. It has been demonstrated that whenever variability of soil properties over an experimental field is high, treatment comparisons should be preceded by an analysis of the background variation to improve the efficiency of the experiment.
... The tractor is a standard orchard tractor that has been retrofitted with additional sensors and computing power (Griepentrog et al., 2009). A Sick laser scanner mounted in front of the robot scans a maximum of 8m for 180degs with a configurable resolution of 0.5 or 1deg at ∼ 70Hz. ...
Autonomous robots require many types of information to obtain intelligent and safe behaviours. For outdoor operations, semantic mapping is essential and this paper proposes a stochastic automaton to localise the robot within the semantic map. For correct modelling and classification under uncertainty, this paper suggests quantising robotic perceptual features, according to a probabilistic description, and then optimising the quantisation. The proposed method is compared with other state-of-the-art techniques that can assess the confidence of their classification. Data recorded on an autonomous agricultural robot are used for verification and the new method is shown to compare very favourably with existing ones.Research highlights► Safe outdoor autonomous operations using fault tolerant semantic mapping. ► Stochastic automaton to model environment-distinctive areas and topological relations. ► Optimised quantisation of perceptual features according to probabilistic descriptions. ► Comparison with existing state of the art using an autonomous agricultural robot.
... The software has been proved that it can control robots powered by combustion engines as well by electric motors. Furthermore it has been demonstrated that machine safety can be improved by adding dedicated functionality (Griepentrog et al., 2009). ...
Research within agricultural technology focuses mainly on increasing the efficiency of crop production. Electric powered machines have several advantages. The machine control is much easier in terms of sensor integration, active navigation and task application compared with traditional machine types. Furthermore, low machine weights and the use of renewable energy to provide the necessary energy contribute to soil protection and low emission performance. The aim of the paper was to describe the design, the control and the renewable energy supply for a small electric powered robot for outdoor field monitoring and other operations. Furthermore the energy consumption for the different operations scenarios was determined based on power consumption measurements for the basic navigation modes. Additionally two different charging scenarios have been investigated. The investigation has shown that it is possible to power a robot using PV cells for an operation time of 11 to 13 hours. The PV charging solutions are expensive compared with using the public power grid. They are only viable when there is no access to the grid.
A state feedback navigation control system based on a virtual Ackerman steering model is proposed in this study to address the problems of the poor smoothness of steering control and low control accuracy of tracked vehicles. The proposed system uses a real-time dynamic positioning global navigation satellite system. Furthermore, it incorporates cubic spline interpolation to smoothen a predetermined path. In addition, a path-tracking control method based on pole assignment, virtual Ackerman steering control model of a single-cylinder diesel-engine-powered tracked vehicle, and forward-steering proportional control method based on the principle of pulse-width modulation were designed. Simulations and field experiments were performed to test the application of the proposed system. The experimental results indicated that the absolute average and standard deviation of the path waypoint interval decreased from 0.227 and 0.348 m to 0.018 and 0.015 m, respectively. In 5- and 6-m-radius-circular and straight-line path-tracking simulations, the average error in path tracking was less than 0.002 m. For path tracking in an orchard environment, the average tracking error and standard error deviation between tree rows were 0.051 and 0.084 m, respectively. These results indicate that the proposed control system enable significantly stable control of single-cylinder diesel-engine-powered tracked vehicles, and its control accuracy meets the operational objectives of tracked vehicles.
The robots are developed to support or replace the humans by accomplishing repetitive, risky, and untidy tasks. There are various applications of robots in agriculture, defense, industry, and other fields. Extensive research has been conducted in the past few decades on the automation of greenhouse operation and agriculture robots. The key things blocking the commercialization of agricultural operations by robotics are adverse interference, unstructured environment, diversified and complicated operation processes. Some kinds of agriculture robots have achieved success in recent years due to the Internet of Things, automation, and information techniques. The research hotspots in agriculture robots are guidance, navigation, mapping, localization, object recognition, location, and also the collaboration operations. This study presents recent applications and development in the field of agriculture robots. The infield navigation algorithms, detection of pests, and optimization of robots in terms of fuel and power are investigated. The automated machinery of agriculture requires the path of movement. The evaluation is conducted of algorithms which can work without GPS. The design of the insect monitoring system is discussed based on image processing techniques. Agriculture vehicles using fossil fuel generate a huge amount of pollution. The solutions to reduce atmospheric pollutants are investigated.
Today, agricultural vehicles are available that can automatically perform tasks such as weed detection and spraying, mowing, and sowing while being steered automatically. However, for such systems to be fully autonomous and self-driven, not only their specific agricultural tasks must be automated. An accurate and robust perception system automatically detecting and avoiding all obstacles must also be realized to ensure safety of humans, animals, and other surroundings. In this paper, we present a multi-modal obstacle and environment detection and recognition approach for process evaluation in agricultural fields. The proposed pipeline detects and maps static and dynamic obstacles globally, while providing process-relevant information along the traversed trajectory. Detection algorithms are introduced for a variety of sensor technologies, including range sensors (lidar and radar) and cameras (stereo and thermal). Detection information is mapped globally into semantical occupancy grid maps and fused across all sensors with late fusion, resulting in accurate traversability assessment and semantical mapping of process-relevant categories (e.g., crop, ground, and obstacles). Finally, a decoding step uses a Hidden Markov model to extract relevant process-specific parameters along the trajectory of the vehicle, thus informing a potential control system of unexpected structures in the planned path. The method is evaluated on a public dataset for multi-modal obstacle detection in agricultural fields. Results show that a combination of multiple sensor modalities increases detection performance and that different fusion strategies must be applied between algorithms detecting similar and dissimilar classes.
