חיפוש מתקדם
Biosystems Engineering
Clément Vigneault
Department of Bioresource Engineering, Macdonald Campus, McGill University, Sainte-Anne-de-Bellevue, Québec, Canada
 
 

This part of our review of the research, developments and innovation in agricultural robots for field operations, focuses on characteristics, performance measures, agricultural tasks and operations. The application of robots to a variety of field operations has been widely demonstrated. A key feature of agricultural robots is that they must operate in unstructured environments without impairing the quality of work currently achieved. Designs, developments and evaluations of agricultural robots are diverse in terms of objectives, structures, methods, techniques, and sensors. Standardisation of terms, system-performance measures and methodologies, and adequacy of technological requirements are vital for comparing robot performance and technical progress. Factors limiting commercialisation and assimilation of agricultural autonomous robot systems are unique to each system and to each task. However, some common gaps need to be filled to suit unstructured, dynamic environments; e.g. poor detection performance, inappropriate decision-making and low action success rate. Research and development of versatile and adaptive algorithms, integrated into multi-sensor platforms, is required. Cycle time must be reduced and production rate increased to justify economic use. Improved wholeness or integration of all sub-systems will enable sustainable performance and complete task operation. Research must focus on each of these gaps and factors that limit commercialisation of agricultural robotics. Research needs to focus on the field use of autonomous or human–robot systems, the latter being a reasonable step toward fully autonomous robots. More robust, reliable information-acquisition systems, including sensor-fusion algorithms and data analysis, should be suited to the dynamic conditions of unstructured agricultural environments.

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תנאי שימוש
Agricultural robots for field operations. Part 2: Operations and systems
153
Clément Vigneault
Department of Bioresource Engineering, Macdonald Campus, McGill University, Sainte-Anne-de-Bellevue, Québec, Canada
 
 
Agricultural robots for field operations. Part 2: Operations and systems

This part of our review of the research, developments and innovation in agricultural robots for field operations, focuses on characteristics, performance measures, agricultural tasks and operations. The application of robots to a variety of field operations has been widely demonstrated. A key feature of agricultural robots is that they must operate in unstructured environments without impairing the quality of work currently achieved. Designs, developments and evaluations of agricultural robots are diverse in terms of objectives, structures, methods, techniques, and sensors. Standardisation of terms, system-performance measures and methodologies, and adequacy of technological requirements are vital for comparing robot performance and technical progress. Factors limiting commercialisation and assimilation of agricultural autonomous robot systems are unique to each system and to each task. However, some common gaps need to be filled to suit unstructured, dynamic environments; e.g. poor detection performance, inappropriate decision-making and low action success rate. Research and development of versatile and adaptive algorithms, integrated into multi-sensor platforms, is required. Cycle time must be reduced and production rate increased to justify economic use. Improved wholeness or integration of all sub-systems will enable sustainable performance and complete task operation. Research must focus on each of these gaps and factors that limit commercialisation of agricultural robotics. Research needs to focus on the field use of autonomous or human–robot systems, the latter being a reasonable step toward fully autonomous robots. More robust, reliable information-acquisition systems, including sensor-fusion algorithms and data analysis, should be suited to the dynamic conditions of unstructured agricultural environments.

Scientific Publication
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