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Automating leaf manipulation in agricultural settings faces significant challenges, including the variability of plant morphologies and deformable leaves. We propose a novel hybrid geometric-neural approach for autonomous leaf grasping that…

机器人学 · 计算机科学 2025-05-20 Srecharan Selvam

Most existing robotic harvesters utilize a unimanual approach; a single arm grasps the crop and detaches it, either via a detachment movement, or by cutting its stem with a specially designed gripper/cutter end-effector. However, such…

机器人学 · 计算机科学 2022-09-14 Sotiris Stavridis , Dimitrios Papageorgiou , Leonidas Droukas , Zoe Doulgeri

In response to the growing challenges of manual labor and efficiency in warehouse operations, Amazon has embarked on a significant transformation by incorporating robotics to assist with various tasks. While a substantial number of robots…

机器人学 · 计算机科学 2025-07-30 Owais Ahmed , M Huzaifa , M Areeb , Hamza Ali Khan

Mobile robots are increasingly utilized in agriculture to automate labor-intensive tasks such as weeding, sowing, harvesting and soil analysis. Recently, agricultural robots have been developed to detect and remove weeds using mechanical…

Automated apple harvesting has attracted significant research interest in recent years due to its potential to revolutionize the apple industry, addressing the issues of shortage and high costs in labor. One key technology to fully enable…

计算机视觉与模式识别 · 计算机科学 2023-03-10 Pengyu Chu , Zhaojian Li , Kaixiang Zhang , Dong Chen , Kyle Lammers , Renfu Lu

Autonomous crop monitoring is a difficult task due to the complex structure of plants. Occlusions from leaves can make it impossible to obtain complete views about all fruits of, e.g., pepper plants. Therefore, accurately estimating the…

机器人学 · 计算机科学 2022-03-30 Salih Marangoz , Tobias Zaenker , Rohit Menon , Maren Bennewitz

Robotic assistance for experimental manipulation in the life sciences is expected to enable favorable outcomes, regardless of the skill of the scientist. Experimental specimens in the life sciences are subject to individual variability and…

机器人学 · 计算机科学 2025-11-11 Enduo Zhao , Murilo M. Marinho , Kanako Harada

Crop detection is integral for precision agriculture applications such as automated yield estimation or fruit picking. However, crop detection, e.g., apple detection in orchard environments remains challenging due to a lack of large-scale…

计算机视觉与模式识别 · 计算机科学 2025-03-17 Robert Johanson , Christian Wilms , Ole Johannsen , Simone Frintrop

Fruit harvesting poses a significant labor and financial burden for the industry, highlighting the critical need for advancements in robotic harvesting solutions. Machine vision-based fruit detection has been recognized as a crucial…

计算机视觉与模式识别 · 计算机科学 2024-07-09 Jiajia Li , Kyle Lammers , Xunyuan Yin , Xiang Yin , Long He , Renfu Lu , Zhaojian Li

Robots are increasingly present in modern industry and also in everyday life. Their applications range from health-related situations, for assistance to elderly people or in surgical operations, to automatic and driver-less vehicles (on…

Neural networks performance has been significantly improved in the last few years, at the cost of an increasing number of floating point operations per second (FLOPs). However, more FLOPs can be an issue when computational resources are…

计算机视觉与模式识别 · 计算机科学 2022-12-08 Thibault Castells , Seul-Ki Yeom

This paper provides an overview of how recent advances in machine learning and the availability of data from earth observing satellites can dramatically improve our ability to automatically map croplands over long period and over large…

计算机视觉与模式识别 · 计算机科学 2019-04-10 Xiaowei Jia , Ankush Khandelwal , Vipin Kumar

Strawberries naturally grow in clusters, interwoven with leaves, stems, and other fruits, which frequently leads to occlusion. This inherent growth habit presents a significant challenge for robotic picking, as traditional…

机器人学 · 计算机科学 2026-02-17 Zhenghao Fei , Wenwu Lu , Linsheng Hou , Chen Peng

Machine vision is critical to robotics due to a wide range of applications which rely on input from visual sensors such as autonomous mobile robots and smart production systems. To create the smart homes and systems of tomorrow, an overview…

计算机视觉与模式识别 · 计算机科学 2019-05-10 Javad Ghofrani , Robert Kirschne , Daniel Rossburg , Dirk Reichelt , Tom Dimter

Estimating accurate and reliable fruit and vegetable counts from images in real-world settings, such as orchards, is a challenging problem that has received significant recent attention. Estimating fruit counts before harvest provides…

计算机视觉与模式识别 · 计算机科学 2022-08-25 Nicolai Häni , Pravakar Roy , Volkan Isler

Modern herbicide application in agricultural settings typically relies on either large scale sprayers that dispense herbicide over crops and weeds alike or portable sprayers that require labor intensive manual operation. The former method…

Manual pruning of radiata pine, a species of major economic importance to New Zealand forestry, is hazardous, labour-intensive, and increasingly constrained by workforce shortages. Existing autonomous pruning platforms typically rely on…

计算机视觉与模式识别 · 计算机科学 2026-05-12 Yida Lin , Bing Xue , Mengjie Zhang , Sam Schofield , Richard Green

Autonomous harvesting may provide a viable solution to mounting labor pressures in the United States's strawberry industry. However, due to bottlenecks in machine perception and economic viability, a profitable and commercially adopted…

机器人学 · 计算机科学 2019-05-03 Jonathon Sather , Xiaozheng Jane Zhang

Surface cracks in infrastructure can lead to severe deterioration and expensive maintenance if not efficiently repaired. Manual repair methods are labor-intensive, time-consuming, and imprecise. While advancements in robotic perception and…

机器人学 · 计算机科学 2025-08-13 Joshua Genova , Eric Cabrera , Vedhus Hoskere

In precision crop protection, (target-orientated) object detection in image processing can help navigate Unmanned Aerial Vehicles (UAV, crop protection drones) to the right place to apply the pesticide. Unnecessary application of non-target…

计算机视觉与模式识别 · 计算机科学 2021-03-09 Zhenwang Qin , Wensheng Wang , Karl-Heinz Dammer , Leifeng Guo , Zhen Cao