Topic: ai2thor-environment Goto Github
Some thing interesting about ai2thor-environment
Some thing interesting about ai2thor-environment
ai2thor-environment,ManipulaTHOR, a framework that facilitates visual manipulation of objects using a robotic arm
Organization: allenai
Home Page: https://ai2thor.allenai.org/manipulathor
ai2thor-environment,Evaluating pre-trained navigation agents under corruptions
Organization: allenai
Home Page: https://prior.allenai.org/projects/robustnav
ai2thor-environment,Learning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)
Organization: allenai
ai2thor-environment,Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
User: erfan-ashtari
ai2thor-environment,Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
Organization: our-projects-github
ai2thor-environment,3D household task-based dataset created using customised AI2-THOR.
User: samsonyubaijian
ai2thor-environment,Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
User: shirin-chehelgami
ai2thor-environment,Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"
Organization: themtank
Home Page: http://www.themtank.org
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