The adoption of autonomous driving technologies in agriculture is accelerating rapidly. The sharp decline in the farming population has led to severe rural depopulation. The agricultural population, which stood at 9.76 million in 2020, is projected to decrease to 8.45 million by 2050. This decline directly reduces agricultural productivity and could lead to the collapse of the agricultural industry. In response, autonomous farming machinery and smart farms have been proposed as key solutions. Autonomous farming machines apply self-driving kits to traditional tractors, enabling unmanned operation and driving innovation in cultivation.
[Fig] Rural Population Forecast
The core technologies of autonomous farming machinery are (1) path generation, (2) control, and (3) situational awareness. Path generation technology uses GPS and LiDAR to set waypoints within the working field and generate the optimal driving route. Control technology involves devices that manage driving, operation, and steering to provide precise and efficient maneuvering. Situational awareness technology uses LiDAR sensors and GPS to detect and respond to anomalies within the working environment. Currently, leading companies in autonomous agricultural machinery provide components such as controllers and steering control wheels to enable self-driving functionality.
[Fig] Technological Stages of Autonomous Agricultural Machinery
Korean company Agmo Co., Ltd. (CEOs: Seungjin Park and Chanwoo Jeon) successfully raised 1.5 billion KRW in Pre-A funding with its tractor-mounted autonomous driving solution. Agmo’s solution reduces labor and increases productivity by generating optimized paths for various types of farmland operations. It can be attached to multiple types of equipment, including tractors, rice transplanters, and cultivators, allowing diverse agricultural tasks to be performed efficiently within limited farmland. The system analyzes the soil and crop conditions within the working area and provides the most suitable autonomous driving solution. Based on this investment, Agmo plans to enter domestic and Asian markets characterized by small, irregular farmlands that require frequent turning.
[Fig] Agmo Co., Ltd.’s Autonomous Farming Kit and Solution
Another active domestic developer is Gint Co., Ltd. (CEO: Yonghyun Kim), a leading autonomous farming machinery company holding 56 patents. Gint has developed technology that integrates situational awareness and autonomous driving for emergency response. Although agricultural machinery has been considered less complex than autonomous cars, commercialization has been hindered by weak emergency handling and monitoring capabilities. Gint solved these problems with its proprietary situational-awareness algorithm and autonomous emergency-response system. Backed by this innovation, the company successfully raised 16.5 billion KRW (Series B).
[Fig] Gint Co., Ltd.’s Autonomous Farming Kit and Solution
Government support for autonomous farming machinery adoption is also active. As part of the Digital New Deal policy, autonomous agricultural machinery has been included as a key component in the transition to digital agriculture. Local governments are conducting pilot projects, with Jeollanam-do Province leading implementation efforts. The province plans to introduce autonomous tractors by 2024, linking them with farm machinery leasing programs to deploy directly in the field. It is also establishing an Innovation Valley for smart farm adoption and aims to boost agricultural productivity through the deployment of autonomous machinery.
#AutonomousFarmingMachinery #AutonomousDriving #AgriculturalMachinery #SmartFarm
The adoption of autonomous driving technologies in agriculture is accelerating rapidly. The sharp decline in the farming population has led to severe rural depopulation. The agricultural population, which stood at 9.76 million in 2020, is projected to decrease to 8.45 million by 2050. This decline directly reduces agricultural productivity and could lead to the collapse of the agricultural industry. In response, autonomous farming machinery and smart farms have been proposed as key solutions. Autonomous farming machines apply self-driving kits to traditional tractors, enabling unmanned operation and driving innovation in cultivation.
[Fig] Rural Population Forecast
The core technologies of autonomous farming machinery are (1) path generation, (2) control, and (3) situational awareness. Path generation technology uses GPS and LiDAR to set waypoints within the working field and generate the optimal driving route. Control technology involves devices that manage driving, operation, and steering to provide precise and efficient maneuvering. Situational awareness technology uses LiDAR sensors and GPS to detect and respond to anomalies within the working environment. Currently, leading companies in autonomous agricultural machinery provide components such as controllers and steering control wheels to enable self-driving functionality.
[Fig] Technological Stages of Autonomous Agricultural Machinery
Korean company Agmo Co., Ltd. (CEOs: Seungjin Park and Chanwoo Jeon) successfully raised 1.5 billion KRW in Pre-A funding with its tractor-mounted autonomous driving solution. Agmo’s solution reduces labor and increases productivity by generating optimized paths for various types of farmland operations. It can be attached to multiple types of equipment, including tractors, rice transplanters, and cultivators, allowing diverse agricultural tasks to be performed efficiently within limited farmland. The system analyzes the soil and crop conditions within the working area and provides the most suitable autonomous driving solution. Based on this investment, Agmo plans to enter domestic and Asian markets characterized by small, irregular farmlands that require frequent turning.
[Fig] Agmo Co., Ltd.’s Autonomous Farming Kit and Solution
Another active domestic developer is Gint Co., Ltd. (CEO: Yonghyun Kim), a leading autonomous farming machinery company holding 56 patents. Gint has developed technology that integrates situational awareness and autonomous driving for emergency response. Although agricultural machinery has been considered less complex than autonomous cars, commercialization has been hindered by weak emergency handling and monitoring capabilities. Gint solved these problems with its proprietary situational-awareness algorithm and autonomous emergency-response system. Backed by this innovation, the company successfully raised 16.5 billion KRW (Series B).
[Fig] Gint Co., Ltd.’s Autonomous Farming Kit and Solution
Government support for autonomous farming machinery adoption is also active. As part of the Digital New Deal policy, autonomous agricultural machinery has been included as a key component in the transition to digital agriculture. Local governments are conducting pilot projects, with Jeollanam-do Province leading implementation efforts. The province plans to introduce autonomous tractors by 2024, linking them with farm machinery leasing programs to deploy directly in the field. It is also establishing an Innovation Valley for smart farm adoption and aims to boost agricultural productivity through the deployment of autonomous machinery.
#AutonomousFarmingMachinery #AutonomousDriving #AgriculturalMachinery #SmartFarm