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Current agriculture and farming industries are able to reap advancements in robotics and automation technology to harvest fruits and vegetables using robots with adaptive grasping forces based on the compliance or softness of the fruit or…

机器人学 · 计算机科学 2024-12-24 Shahid Ansari , Mahendra Kumar Gohil , Bishakh Bhattacharya

Selective fruit harvesting is a challenging manipulation problem due to occlusions and clutter arising from plant foliage. A harvesting gripper should i) have a small cross-section, to avoid collisions while approaching the fruit; ii) have…

机器人学 · 计算机科学 2024-08-14 Alejandro Velasquez , Cindy Grimm , Joseph R. Davidson

The automation of fruit harvesting has gained increasing significance in response to rising labor shortages. A sensorized gripper is a key component of this process, which must be compact enough for confined spaces, able to stably grasp…

机器人学 · 计算机科学 2026-02-24 Ruohan Zhang , Mohammad Amin Mirzaee , Wenzhen Yuan

This paper presents an autonomous tomato-harvesting system built around a hybrid robotic gripper that combines six soft auxetic fingers with a rigid exoskeleton and a latex basket to achieve gentle, cage-like grasping. The gripper is driven…

机器人学 · 计算机科学 2025-12-04 Shahid Ansari , Mahendra Kumar Gohil , Yusuke Maeda , Bishakh Bhattacharya

As global demand for fruits and vegetables continues to rise, the agricultural industry faces challenges in securing adequate labor. Robotic harvesting devices offer a promising solution to solve this issue. However, harvesting delicate…

机器人学 · 计算机科学 2025-01-15 Johannes F. Elfferich , Ebrahim Shahabi , Cosimo Della Santina , Dimitra Dodou

This paper presents a novel cable-driven gripper with perception capabilities for autonomous harvesting of strawberries. Experiments show that the gripper allows for more accurate and faster picking of strawberries compared to existing…

机器人学 · 计算机科学 2018-04-27 Ya Xiong , Pal Johan From , Volkan Isler

The agricultural sector is rapidly evolving to meet growing global food demands, yet tasks like fruit and vegetable handling remain labor-intensive, causing inefficiencies and post-harvest losses. Automation, particularly selective…

机器人学 · 计算机科学 2025-10-14 Shahid Ansari , Vivek Gupta , Bishakh Bhattacharya

In the robotic crop harvesting environment, foreign objects intrusion in the gripper workspace is frequently occurring and unignorable, however, rarely addressed. This paper presents a novel intelligent robotic grasping method capable of…

机器人学 · 计算机科学 2021-10-19 Hongyu Zhou , Xing Wang , Hanwen Kang , Chao Chen

Global berry production and consumption have significantly increased in recent years, coinciding with increased consumer awareness of the health-promoting benefits of berries. Among them, fresh market blackberries and raspberries are…

机器人学 · 计算机科学 2021-03-10 Anthony L. Gunderman , Jeremy Collins , Andrea Myer , Renee Threlfall , Yue Chen

Growing global demand for food, coupled with continuing labor shortages, motivates the need for automated agricultural harvesting. While some specialty crops (e.g., apples, peaches, blueberries) can be harvested via existing harvesting…

机器人学 · 计算机科学 2023-02-08 Alex Qiu , Claire Young , Anthony Gunderman , Milad Azizkhani , Yue Chen , Ai-Ping Hu

Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional rigid grippers typically rely on increasing the normal forces to secure an object,…

Handling oversized, variable-shaped, or delicate objects in transportation, grasping tasks is extremely challenging, mainly due to the limitations of the gripper's shape and size. This paper proposes a novel gripper, Lasso Gripper. Inspired…

机器人学 · 计算机科学 2025-06-18 Qiyuan Qiao , Yu Wang , Xiyu Fan , Peng Lu

Soft grippers have excellent adaptability for a variety of objects and tasks. Jamming-based variable stiffness materials can further increase soft grippers' gripping force and capacity. Previous universal grippers enabled by granular…

机器人学 · 计算机科学 2023-04-13 Yuchen Zhao , Yifan Wang

Novel robotic grippers have captured increasing interests recently because of their abilities to adapt to varieties of circumstances and their powerful functionalities. Differing from traditional gripper with mechanical components-made…

A key challenge in robotics is to create efficient methods for grasping objects with diverse shapes, sizes, poses, and properties. Grasping with hand-like end effectors often requires careful selection of hand orientation and finger…

机器人学 · 计算机科学 2019-12-17 Yufei Hao , Shantonu Biswas , Elliot Hawkes , Tianmiao Wang , Mengjia Zhu , Li Wen , Yon Visell

Robotic manipulation of fresh fruits and vegetables, including the grasping of multiple loose items, has a strong industrial need but it still is a challenging task for robotic manipulation. This paper outlines the distinctive manipulation…

We propose a novel tri-fingered soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers adaptively conform to object shapes…

机器人学 · 计算机科学 2020-10-23 Dimuthu D. Arachchige , Yue Chen , Ian D. Walker , Isuru S. Godage

Over the past few decades, efforts have been made towards robust robotic grasping, and therefore dexterous manipulation. The soft gripper has shown their potential in robust grasping due to their inherent properties-low, control complexity,…

机器人学 · 计算机科学 2020-12-08 Linhan Yang , Xudong Han , Weijie Guo , Zixin Zhang , Fang Wan , Jia Pan , Chaoyang Song

Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional grippers often rely on applying high normal forces, which can cause damage to objects.…

Soft grippers are receiving growing attention due to their compliance-based interactive safety and dexterity. Hybrid gripper (soft actuators enhanced by rigid constraints) is a new trend in soft gripper design. With right structural…

机器人学 · 计算机科学 2021-10-20 Wenpei Zhu , Chenghua Lu , Qule Zheng , Zhonggui Fang , Haichuan Che , Kailuan Tang , Mingchao Zhu , Sicong Liu , Zheng Wang
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