Results 11 to 20 of about 1,523,083 (336)
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control [PDF]
Conference on Robot Learning, 2023 We study how vision-language models trained on Internet-scale data can be incorporated directly into end-to-end robotic control to boost generalization and enable emergent semantic reasoning.
Anthony Brohan +45 more
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VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models [PDF]
Conference on Robot Learning, 2023 Large language models (LLMs) are shown to possess a wealth of actionable knowledge that can be extracted for robot manipulation in the form of reasoning and planning. Despite the progress, most still rely on pre-defined motion primitives to carry out the
Wenlong Huang +5 more
semanticscholar +1 more source
Language to Rewards for Robotic Skill Synthesis [PDF]
Conference on Robot Learning, 2023 Large language models (LLMs) have demonstrated exciting progress in acquiring diverse new capabilities through in-context learning, ranging from logical reasoning to code-writing.
Wenhao Yu +19 more
semanticscholar +1 more source
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action [PDF]
Conference on Robot Learning, 2022 Goal-conditioned policies for robotic navigation can be trained on large, unannotated datasets, providing for good generalization to real-world settings.
Dhruv Shah +3 more
semanticscholar +1 more source
Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces [PDF]
International Conference on Human Factors in Computing Systems, 2022 This paper contributes to a taxonomy of augmented reality and robotics based on a survey of 460 research papers. Augmented and mixed reality (AR/MR) have emerged as a new way to enhance human-robot interaction (HRI) and robotic interfaces (e.g., actuated
R. Suzuki +4 more
semanticscholar +1 more source
Trust in Robot–Robot Scaffolding
IEEE Transactions on Cognitive and Developmental Systems, 2023 The study of robot trust in humans and other agents is not explored widely despite its importance for the near future human-robot symbiotic societies. Here, we propose that robots should trust partners that tend to reduce their computational load, which is analogous to human cognitive load.
Murat Kirtay +3 more
openaire +3 more sources
Cureus, 2023 Robotic surgery, a groundbreaking advancement in medical technology, has redefined the landscape of surgical procedures. This comprehensive overview explores the multifaceted world of robotic surgery, encompassing its definition, historical development ...
K. Reddy +5 more
semanticscholar +1 more source
A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation
Italian National Conference on Sensors, 2023 Robotic manipulation challenges, such as grasping and object manipulation, have been tackled successfully with the help of deep reinforcement learning systems.
Dong-Ki Han +3 more
semanticscholar +1 more source
Handover Control for Human-Robot and Robot-Robot Collaboration [PDF]
Frontiers in Robotics and AI, 2021 Modern scenarios in robotics involve human-robot collaboration or robot-robot cooperation in unstructured environments. In human-robot collaboration, the objective is to relieve humans from repetitive and wearing tasks. This is the case of a retail store, where the robot could help a clerk to refill a shelf or an elderly customer to pick an item from ...
Costanzo M., De Maria G., Natale C.
openaire +4 more sources
Past, Present, and Future of Aerial Robotic Manipulators
IEEE Transactions on robotics, 2022 This article analyzes the evolution and current trends in aerial robotic manipulation, comprising helicopters, conventional underactuated multirotors, and multidirectional thrust platforms equipped with a wide variety of robotic manipulators capable of ...
A. Ollero +4 more
semanticscholar +1 more source