Evidence map›Paper›PMID 42688725›Full record

ReviewFrontiers in plant science2026

Heterogeneous agricultural robots: a review of collaborative sensing and control, challenges and opportunities.

Rongrong Gu, Songda Luan, Yunming Zhao, Shengyi Zhao, Xi Kan, Yuxuan Ma, Tao Teng, Yuxin Sun, Chengyuan Li, Xudong Sun and 1 more

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Rongrong GuSchool of IoT Engineering, Wuxi University, Wuxi, China.
Songda LuanSchool of IoT Engineering, Wuxi University, Wuxi, China.
Yunming ZhaoCollege of Control Science and Engineering, Zhejiang University, Hangzhou, China.
Shengyi ZhaoSchool of Agricultural Engineering, Jiangsu University, Zhenjiang, China.
Xi KanSchool of IoT Engineering, Wuxi University, Wuxi, China.
Yuxuan MaSchool of IoT Engineering, Wuxi University, Wuxi, China.
Tao TengSchool of IoT Engineering, Wuxi University, Wuxi, China.
Yuxin SunSchool of IoT Engineering, Wuxi University, Wuxi, China.
Chengyuan LiSchool of IoT Engineering, Wuxi University, Wuxi, China.
Xudong SunCollege of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China.
Jizhang WangSchool of Agricultural Engineering, Jiangsu University, Zhenjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A critical shift towards improved efficiency is currently taking place in modern agriculture, sustainability, and intelligence, driven by population growth, resource constraints, labor shortages, and increasing environmental pressure. Agricultural robots, especially heterogeneous robotic systems, have emerged as key enablers of this transformation by enabling precise, automated, and large-scale operations. This paper presents a comprehensive review of collaborative sensing and control technologies for heterogeneous agricultural robots working in both structured agricultural environments (greenhouses, orchards, and facility cultivation) and representative field farming scenarios. Focusing on recent advances over the past three years, we systematically analyze five representative robotic platforms: sprinkler irrigation robots, unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), agricultural robotic arms, and underground robots, from the perspectives of sensing, control, and cooperative operation. The review highlights key control methodologies, including intelligent path planning, adaptive and learning-based control, visual navigation, multi-sensor fusion, and energy-aware optimization. Furthermore, air-ground-underground integrated systems are discussed as an emerging paradigm for full-space agricultural coverage. Beyond technological progress, this paper identifies critical challenges in heterogeneous agricultural robot systems, including cooperative communication reliability, real-time safe control under dynamic environments, energy and endurance constraints, and system-level security. Finally, future research directions are outlined, emphasizing integrated communication and sensing, dual-arm and multi-arm collaborative manipulation, and heterogeneous multi-robot cooperative control frameworks.

Indexed as

air–ground–underground integrationcollaborative sensing and controlheterogeneous agricultural robotsintelligent precision agriculturemulti-agent systems

Identifiers

PMID42688725
PMCPMC13536900

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.