Self-Learning Orchard Picking Robot Swarm OrchardBot Deployed in Japan: Picking Efficiency Reaches 8x Human Workers

Japanese agricultural robotics company Inaho announced on September 3 that its OrchardBot orchard picking robot swarm completed its first large-scale commercial deployment in apple orchards in Hirosaki, Aomori Prefecture. Twenty OrchardBot robots worked collaboratively to pick 200 tons of apples in one week, achieving 8 times the efficiency of human picking crews.

Each OrchardBot features a six-axis robotic arm, 3D vision system, and soft gripper. The vision system uses an AI model to identify apple ripeness, size, and position at individual fruit precision. The soft gripper uses a biomimetic design that picks fruit with exactly the right amount of force without causing damage.

OrchardBot's key innovation is its "self-learning" capability. At the start of picking season, the robot's identification accuracy for a specific apple variety is approximately 85%. After one week of autonomous learning and model updates, accuracy improves to over 98%. The system also learns the orchard's terrain, tree layout, and fruit distribution patterns, continuously optimizing route planning.

Inaho's CEO said: "Japan's agriculture faces severe labor shortages. Aomori's apple picking season requires about 20,000 temporary workers, but in recent years available labor has been less than half of demand. OrchardBot isn't replacing farmers—it's filling the labor gap."