Robotic Platform for Horticulture: Assessment Methodology and Increasing the Level of Autonomy.

Area of Science:

• Agricultural Engineering
• Robotics
• Horticulture Automation

Background:

• Rapid advancements in agricultural automation, particularly in horticulture, necessitate improved robotic technologies.
• A gap exists in methodological frameworks for evaluating the effectiveness of robotic systems in agriculture.
• There is a growing need to enhance the functional capabilities of mobile robots in horticultural applications.

Purpose of the Study:

• To increase the autonomy of robotic platforms for apple fruit picking using a novel methodology.
• To establish a system of factors for assessing the effectiveness of robot implementation in horticulture.
• To develop an integrated control system for robotic platforms utilizing onboard data processing.

Main Methods:

• Expert surveys were conducted with 30 enterprises and scientists specializing in robotic platforms in horticulture.
• A concordance coefficient method (expert analysis) was employed to rank 18 identified efficiency factors.
• Development of a control system for an autonomous robotic wheeled platform using inertial and satellite navigation.

Main Results:

• A ranked list of 18 efficiency factors was obtained through expert evaluation.
• The three most significant factors identified were: degree of work autonomy, positioning accuracy, and recognition accuracy.
• A control system was developed for autonomous robotic platform movement, enabling automated technological operations in horticulture.

Conclusions:

• The study successfully developed a new method to increase robotic platform autonomy for apple harvesting.
• Key factors for evaluating robotic system effectiveness in horticulture were identified and ranked.
• The developed control system and software facilitate automated operations, enhancing efficiency in intensive horticultural environments.