Gemini Robotics in Agriculture: Applications, Models, Fruit Industry, and Future Perspectives
Year: 2026
Type: preprint
Abstract: Agricultural robotics is progressing from task-specific automation toward embodied systems that integrate multimodal perception, language, reasoning, and physical action. This chapter reviews Gemini Robotics and closely related vision-language model (VLM) and vision-language-action (VLA) developments in the context of agriculture, with particular emphasis on fruit production. It first presents a conceptual agricultural architecture linking sensing, cognition, decision and control, actuation, connectivity, power and safety. It then examines emerging evidence from language-guided agricultural navigation, spatial-memory systems, occlusion-aware harvest planning, VLA-based strawberry harvesting, obstacle separation and text-prompted multi-fruit picking. The reviewed studies show growing capability in navigation, semantic reasoning and closed-loop manipulation, but also expose important limitations in agricultural validation, cross-crop generalization, action datasets, real-time computing, safety and commercial readiness. For fruit systems, the principal technical challenges remain occlusion, maturity and accessibility assessment, three-dimensional localization, delicate detachment and adaptation across cultivars, canopies and seasons. The chapter therefore proposes a future pathway centered on multimodal agricultural foundation models, edge VLA inference, soft and tactile manipulation, continual learning, natural-language human-robot collaboration and coordinated UAV-UGV-manipulator systems. The Gemini Robotics provides a promising foundation for moving agricultural robots from isolated perception-action pipelines toward general-purpose embodied intelligence, although extensive field validation is required before broad deployment.
Source: Research Square
Authors: mustafa mhamed, Zhao Zhang
Institution: China Agricultural University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225916781