首页|Study Findings from Soochow University Update Knowledge in Robotics (Octopus-Ins pired Soft Robot for Slow Drug Release)

Study Findings from Soochow University Update Knowledge in Robotics (Octopus-Ins pired Soft Robot for Slow Drug Release)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on robotics have bee n published. According to news reporting originating from Suzhou, People's Repub lic of China, by NewsRx correspondents, research stated, "Octopus tentacles are equipped with numerous suckers, wherein the muscles contract and expel air, crea ting a pressure difference." Funders for this research include Natural Science Foundation of Jiangsu Province ; National Natural Science Foundation of China; State Key Laboratory of Robotics And System; Hui-chun Chin And Tsungdao Lee Chinese Undergraduate Research Endow ment. The news correspondents obtained a quote from the research from Soochow Universi ty: "Subsequently, when the muscular tension is released, objects can be securel y adhered to. This mechanism has been widely employed in the development of adhe sive systems. However, most existing octopus-inspired structures are passive and static, lacking dynamic and controllable adhesive switching capabilities and ex cellent locomotion performance. Here, we present an octopus-inspired soft robot (OISR). Attracted by the magnetic gradient field, the suction cup structure insi de the OISR can generate a strong adsorption force, producing dynamically contro llable adsorption and separation in the gastrointestinal (GI) tract. The experim ental results show that the OISR has a variety of controllable locomotion behavi ors, including quick scrolling and rolling motions, generating fast locomotion r esponses, rolling over gastric folds, and tumbling and swimming inside liquids."

Soochow UniversitySuzhouPeople's Rep ublic of ChinaAsiaDrugs and TherapiesEmerging TechnologiesMachine Learni ngRobotRobotics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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年,卷(期):2024.(Jun.24)