Mobile robotics in smart farming: current trends and applications

Area of Science:

• Agricultural Engineering
• Robotics
• Computer Science

Background:

• Arable land scarcity necessitates increased food production, projected by FAO to rise by one-third by 2050.
• Intensive fertilizer use for crop yields negatively impacts food nutritional quality.
• Mobile robots are increasingly used in agriculture for path planning and data gathering to address productivity and sustainability challenges.

Purpose of the Study:

• To review the application of mobile robotics in farming to decrease costs, minimize environmental impact, and optimize harvests.
• To establish the current status, technologies, algorithms, and results of mobile robotics in smart farming.
• To present challenges and propose solutions for advanced smart farming techniques.

Main Methods:

• Review of current mobile robotics applications in agriculture.
• Analysis of technologies including the Internet of Things (IoT), artificial intelligence (AI), artificial vision, and big data.
• Examination of algorithms for path planning, crop information gathering, and multi-objective control.

Main Results:

• Current agricultural robotic systems are often large and expensive due to client-server architectures.
• Mobile robotics, IoT, AI, artificial vision, multi-objective control, and big data are leading smart farming technologies.
• A fully autonomous, low-cost agricultural mobile robotic system independent of a server is a viable technological solution.

Conclusions:

• Mobile robotics offers a pathway to reduce farming costs, environmental impact, and optimize harvests.
• Key enabling technologies for smart farming include IoT, mobile robotics, AI, artificial vision, multi-objective control, and big data.
• Overcoming challenges in environmental conditions, costs, technical requirements, automation, connectivity, and processing power is crucial for widespread adoption.