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Found 9 papers, 1 papers with code
Robotic Constrained Imitation Learning for the Peg Transfer Task in Fundamentals of Laparoscopic Surgery
In this study, we present an implementation strategy for a robot that performs peg transfer tasks in Fundamentals of Laparoscopic Surgery (FLS) via imitation learning, aimed at the development of an autonomous robot for laparoscopic surgery.
CoverLib: Classifiers-equipped Experience Library by Iterative Problem Distribution Coverage Maximization for Domain-tuned Motion Planning
During the query phase, these classifiers are utilized to select an experience that is expected to be adaptable for a given problem.
Continuous Object State Recognition for Cooking Robots Using Pre-Trained Vision-Language Models and Black-box Optimization
By using models that can compute the similarity between images and texts continuously over time, we can capture the state changes of food while cooking.
TrTr: Visual Tracking with Transformer
In this new architecture, features of the template image is processed by a self-attention module in the encoder part to learn strong context information, which is then sent to the decoder part to compute cross-attention with the search image features processed by another self-attention module.
Understanding Action Sequences based on Video Captioning for Learning-from-Observation
We propose a Learning-from-Observation framework that splits and understands a video of a human demonstration with verbal instructions to extract accurate action sequences.
Joint Learning of Instance and Semantic Segmentation for Robotic Pick-and-Place with Heavy Occlusions in Clutter
We present joint learning of instance and semantic segmentation for visible and occluded region masks.
Instance Segmentation of Visible and Occluded Regions for Finding and Picking Target from a Pile of Objects
We present a robotic system for picking a target from a pile of objects that is capable of finding and grasping the target object by removing obstacles in the appropriate order.
Probabilistic 3D Multilabel Real-time Mapping for Multi-object Manipulation
Probabilistic 3D map has been applied to object segmentation with multiple camera viewpoints, however, conventional methods lack of real-time efficiency and functionality of multilabel object mapping.
3D Object Segmentation for Shelf Bin Picking by Humanoid with Deep Learning and Occupancy Voxel Grid Map
Picking objects in a narrow space such as shelf bins is an important task for humanoid to extract target object from environment.
