paper-with-me

Papers

Replaceable Bit-based Gripper for Picking Cluttered Food Items

2026-01-01 · Prashant Kumar, Yukiyasu Domae, Weiwei Wan, Kensuke Harada arxiv

The food packaging industry goes through changes in food items and their weights quite rapidly. These items range from easy-to-pick, single-piece food items to flexible, long and cluttered ones. We propose a replaceable bit-based gripper system to tackle the challenge of weight-based handling of cluttered food items. The gripper features specialized food attachments(bits) that enhance its grasping capabilities, and a belt replacement system allows switching between different food items during packaging operations. It offers a wide range of control options, enabling it to grasp and drop specific weights of granular, cluttered, and entangled foods. We specifically designed bits for two flexible food items that differ in shape: ikura(salmon roe) and spaghetti. They represent the challenging categories of sticky, granular food and long, sticky, cluttered food, respectively. The gripper successfully picked up both spaghetti and ikura and demonstrated weight-specific dropping of these items with an accuracy over 80% and 95% respectively. The gripper system also exhibited quick switching between different bits, leading to the handling of a large range of food items.

📄 PDF Abstract BibTeX arXiv:2601.00305

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

TetraGrip: Sensor-Driven Multi-Suction Reactive Object Manipulation in Cluttered Scenes

2025-03-12 · Paolo Torrado, Joshua Levin, Markus Grotz, Joshua Smith

Warehouse robotic systems equipped with vacuum grippers must reliably grasp a diverse range of objects from densely packed shelves. However, these environments present significant challenges, including occlusions, divers…

Object

Corner-Grasp: Multi-Action Grasp Detection and Active Gripper Adaptation for Grasping in Cluttered Environments

2025-04-02 · Yeong Gwang Son, Seunghwan Um, Juyong Hong, Tat Hieu Bui 외

Robotic grasping is an essential capability, playing a critical role in enabling robots to physically interact with their surroundings. Despite extensive research, challenges remain due to the diverse shapes and properti…

Robotic Grasping

Pose estimation and bin picking for deformable products

2019-11-12 · Benjamin Joffe, Tevon Walker. Remi Gourdon, Konrad Ahlin

Robotic systems in manufacturing applications commonly assume known object geometry and appearance. This simplifies the task for the 3D perception algorithms and allows the manipulation to be more deterministic. However,…

ObjectPose Estimation

Deep Reinforcement Learning for Robotic Pushing and Picking in Cluttered Environment

2023-02-21 · Yuhong Deng, Xiaofeng Guo, Yixuan Wei, Kai Lu 외

In this paper, a novel robotic grasping system is established to automatically pick up objects in cluttered scenes. A composite robotic hand composed of a suction cup and a gripper is designed for grasping the object sta…

Deep Reinforcement LearningObjectreinforcement-learningReinforcement Learning (RL)+1

Towards Reliable Sequential Object Picking in Clutter: The Runner-up Solution to RGMC 2025

2026-06-11 · Wei Yu, Xidan Zhang, Ziyi Zheng, Weijie Kong 외 arxiv

As a long-standing challenge in robotic manipulation, stable and efficient grasping in cluttered environments is of great importance in industrial settings. While recent studies have achieved relatively high success rate…

Object RecognitionRobotic Grasping