Archive 08.02.2024

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Adaptive robot can open all the doors

A small team of roboticists at Carnegie Mellon University has developed a training regimen that allows a robot to start out with limited abilities, such as carrying out a certain task like opening doors or drawers, and to improve as it teaches itself how to modify its techniques when faced with previously unseen challenges.

A deep reinforcement learning approach to enhance autonomous robotic grasping and assembly

Semi-autonomous and autonomous robots are being introduced in a growing number of real-world environments, including industrial settings. Industrial robots could speed up the manufacturing of various products by assisting human workers with basic tasks and lightening their workload.

Exploring the eating experience of a pneumatically-driven edible robot: Perception, taste, and texture

In a landmark study, Associate Professor Yoshihiro Nakata of the University of Electro-Communications, Japan, in collaboration with researchers from Osaka University, conducted research on edible robotics. Published in PLOS ONE, this study is the first to explore the experience of consuming a moving edible robot.

Research team develops metamaterial to enable real-time shape and property control

Inspired by the remarkable adaptability observed in biological organisms like the octopus, a breakthrough has been achieved in the field of soft robotics. A research team, led by Professor Jiyun Kim in the Department of Materials Science and Engineering at UNIST has successfully developed an encodable multifunctional material that can dynamically tune its shape and mechanical properties in real time.
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