An Untethered Soft Robotic Gripper with Adjustable Grasping Modes and Force Feedback

Yang, Yang; Zhu, Honghui; Liu, Jia; Li, Yingtian; Zhou, Jianshu; Ren, Tao; Ren, Yi

doi:10.1109/robio55434.2022.10011866

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…Liang et al combine flexible high-performance tactile sensors with soft prosthetic hand (PSD), enabling intelligent tactile perception for an SPD and can be applied to traditional Chinese medicine pulse diagnosis [36]. Yang et al propose a three-finger soft robotic gripper with a pressure sensor integrated at the end of the finger to perceive force feedback and accommodate different objects [37]. However, these piezoresistive sensors are all schistose structure and lack the ability to conform to the shape of an object and establish adaptive contact like human finger pulp.…”

Section: Introductionmentioning

confidence: 99%

Soft robotic fingers with sensorized pre-charged finger pulp

Zhu,

Yang,

Yan

et al. 2024

Smart Mater. Struct.

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Pneumatically driven soft actuators with sensors have been developing rapidly these years. They can perceive external stimulus and be applied to different scenarios. In this study, we present a novel soft robotic finger with sensorized finger pulp based on sealing a flexible fabric piezoresistive film called Velostat into a pre-charged air bag, which can perceive the contact force with an object based on changes in resistance value of the sensor. The soft sensor mimics human finger pulp and deforms passively according to the shape of objects during grasping, so that it can firmly contact with objects and as such improves the gripper’s grasping stability. Moreover, based on force feedback, the actuator can reduce or increase the input pressure to hold the object and control the contact force precisely. The sensor exhibits a sensitivity of up to 0.328 kPa−1 and can measure pressures ranging from 0 to over 10 kPa. The sensor’s measurement range and sensitivity can be pre-adjusted by regulating the pre-charged pressure during fabrication for different grasping tasks. The response/recovery time of the sensor is 80/60 ms on average. Experiments show that the finger with sensorized pulp can be applied for object softness and size detection, object transport minitoring as well as force control grasping. The proposed soft robotic finger has potential for applications in scenarios that require safe contact and closed-loop control.

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Section: Introductionmentioning

confidence: 99%

Soft robotic fingers with sensorized pre-charged finger pulp

Zhu,

Yang,

Yan

et al. 2024

Smart Mater. Struct.

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show abstract

“…Several studies show that, in principle, robotic hardware is already capable of providing all the necessary functions for household and cooking processes [8,9]. The more challenging part is designing and enabling the grippers to grasp tools and selecting ingredients of the cooking process of varying texture, shape and solidity [10,11]. Another important aspect is safety when using robots in open workspaces in the household environment.…”

Section: Introductionmentioning

confidence: 99%

Robot Cooking—Transferring Observations into a Planning Language: An Automated Approach in the Field of Cooking

Schmitz,

Menz,

Grunau

et al. 2023

Eng

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The recognition of human activities from video sequences and their transformation into a machine-readable form is a challenging task, which is the subject of many studies. The goal of this project is to develop an automated method for analyzing, identifying and processing motion capture data into a planning language. This is performed in a cooking scenario by recording the pose of the acting hand. First, predefined side actions are detected in the dataset using classification. The remaining frames are then clustered into main actions. Using this information, the known initial positions and virtual object tracking, a machine-readable planning domain definition language (PDDL) is generated.

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Artificial intelligence for waste management in smart cities: a review

Fang

Chen

et al. 2023

Environ Chem Lett

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The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste ecosystem, such as the use of artificial intelligence. Here, we review the application of artificial intelligence in waste-to-energy, smart bins, waste-sorting robots, waste generation models, waste monitoring and tracking, plastic pyrolysis, distinguishing fossil and modern materials, logistics, disposal, illegal dumping, resource recovery, smart cities, process efficiency, cost savings, and improving public health. Using artificial intelligence in waste logistics can reduce transportation distance by up to 36.8%, cost savings by up to 13.35%, and time savings by up to 28.22%. Artificial intelligence allows for identifying and sorting waste with an accuracy ranging from 72.8 to 99.95%. Artificial intelligence combined with chemical analysis improves waste pyrolysis, carbon emission estimation, and energy conversion. We also explain how efficiency can be increased and costs can be reduced by artificial intelligence in waste management systems for smart cities.

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An Untethered Soft Robotic Gripper with Adjustable Grasping Modes and Force Feedback

Cited by 4 publications

References 30 publications

Soft robotic fingers with sensorized pre-charged finger pulp

Soft robotic fingers with sensorized pre-charged finger pulp

Robot Cooking—Transferring Observations into a Planning Language: An Automated Approach in the Field of Cooking

Artificial intelligence for waste management in smart cities: a review

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