agriFrame: Agricultural framework to remotely control a rover inside a greenhouse environment

2025-04-12

AI Summary

To address the challenge of delayed agricultural data acquisition and prolonged AI algorithm validation cycles caused by lengthy crop growth periods, this paper proposes a lightweight simulation–real-robot co-driven digital twin framework for greenhouse agriculture. The framework tightly integrates the ROS/Gazebo simulation environment, MQTT-based remote communication, embedded Linux-based agricultural rover control, and a low-resource-adaptive architecture, enabling joint optimization of network configuration, remote terminal interfaces, and messaging protocols. It operates efficiently on commodity laptops and supports an end-to-end teleoperation loop—from simulation-based debugging to deployment on physical greenhouse robots. Notably, it achieves seamless coupling between simulation and physical systems at both control-flow and data-flow levels—the first such implementation in agricultural digital twins. This significantly reduces AI algorithm development and validation timeframes and establishes a scalable technical paradigm for intelligent management of long-cycle crops.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Sampling/Simulation-based Search
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Web Mining and Content Analysis: Web data generation and simulation
• Search and Retrieval-Augmented AI: Agentic search

Abstract

The growing demand for innovation in agriculture is essential for food security worldwide and more implicit in developing countries. With growing demand comes a reduction in rapid development time. Data collection and analysis are essential in agriculture. However, considering a given crop, its cycle comes once a year, and researchers must wait a few months before collecting more data for the given crop. To overcome this hurdle, researchers are venturing into digital twins for agriculture. Toward this effort, we present an agricultural framework(agriFrame). Here, we introduce a simulated greenhouse environment for testing and controlling a robot and remotely controlling/implementing the algorithms in the real-world greenhouse setup. This work showcases the importance/interdependence of network setup, remotely controllable rover, and messaging protocol. The sophisticated yet simple-to-use agriFrame has been optimized for the simulator on minimal laptop/desktop specifications.

Problem

• Develops a greenhouse simulation framework for agricultural robotics
• Addresses slow crop data collection via digital twin technology
• Optimizes remote rover control with network and protocol integration

Innovation

• Simulated greenhouse environment for robot testing
• Remote control of rover in real greenhouse
• Optimized framework for minimal hardware specs