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A visual-linguistic framework that enables open-vocabulary object grasping in robots

To be deployed in a broad range of real-world dynamic settings, robots should be able to successfully complete various manual tasks, ranging from household chores to complex manufacturing or agricultural processes. These manual tasks entail grasping, manipulating and placing objects of different types, which can vary in shape, weight, properties and textures.

The feel of the future: Elevating haptics with advanced dual-rate sampling

Haptic feedback stands as a cornerstone for the authenticity and depth of engagement in virtual reality and teleoperation systems. Yet, existing haptic devices have grappled with the fidelity of replicating tactile properties, hindered by the constraints on their degrees of freedom and expressive range. This limitation has ignited an urgent quest for innovative solutions that can augment the responsiveness and adaptability of haptic systems.

Shared awareness could lead to greener, more ethical, and useful smart machines

The future deployment of AIs and robots in our everyday work and life, from fully automated vehicles, to delivery robots, and AI assistants, could either be done by making increasingly capable agents that can do many tasks, or simpler more narrow agents that are designed for specific tasks.
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