Lab2Field transfer of a robotic raspberry harvester enabled by a soft sensorized physical twin

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Soft robots, compared to rigid robots, possess inherent advantages, including higher degrees of freedom, compliance, and enhanced safety, which have contributed to their increasing application across various fields. Among these benefits, adaptability is pa ...

Leading researchers debate the long-term influence of model-free methods that use large sets of demonstration data to train numerical generative models to control robots. ...

Pronunciation is a critical yet challenging aspect of language acquisition, especially for children. In this work, we propose a new teachable agent system designed to support children's pronunciation learning through a Learning-by-Teaching paradigm to addr ...

Robust in-hand manipulation of objects with movable content requires estimation and prediction of the contents' motion with enough anticipation to allow time to compensate for resulting internal torques. The quick estimation of the objects' dynamics can be ...

Autonomous robots have the potential to fundamentally transform conventional farming methods, e.g. by enabling economically viable farming of sloped arable land. However, navigation on slopes in harsh conditions is challenging for robots as they must be pr ...

Lab2Field transfer of a robotic raspberry harvester enabled by a soft sensorized physical twin

Chat with Graph Search

A Survey on Soft Robot Adaptability: Implementations, Applications, and Prospects [Survey]

“Data will solve robotics and automation: True or false?”: A debate

Learning by Teaching: Designing Teachable Agents to Support Children's Pronunciation Skill Learning

A Predictive Model for Tactile Force Estimation Using Audio-Tactile Data

Automation in steep terrain agriculture: an optimal controller to prevent tipping and slipping of tethered robots on slopes