Object Search

Object search, a crucial task for robotics and computer vision, aims to efficiently locate specific objects within complex environments using visual and/or language-based cues. Current research emphasizes robust object localization in dynamic, cluttered scenes, often employing transformer-based models and leveraging knowledge graphs or large language models to incorporate contextual information and improve search strategies. This field is vital for advancing autonomous systems in various applications, including household robotics, search and rescue, and mobile manipulation, where efficient and reliable object finding is paramount. The development of generalized, robust, and efficient object search methods is a key focus, with recent work exploring both imitation learning from human demonstrations and the development of certifiably robust detection methods against adversarial attacks.