Robot Interaction

Robot interaction research focuses on enabling robots to effectively and naturally interact with humans and their environments, aiming to improve robot capabilities in diverse tasks and settings. Current research emphasizes developing robust models for scene understanding, object manipulation (including leveraging audio-visual data and tactile feedback), and intuitive human-robot interaction design, often employing deep learning architectures like convolutional neural networks and recurrent neural networks. This field is significant for advancing robotics technology, impacting areas such as assistive robotics, education, and industrial automation, while also providing valuable insights into human-computer interaction and cognitive science.