Human Behavior Data Generation
Human Behavior Data Generation
Research Summary
As the rapid development of using reinforced learning in robot manipulation, its’ success depends heavily on the scale of large dataset which doesn’t exist especially in long-horizon bimanual manipulation tasks and collecting these datasets are time-consuming and constrained by experiment equipment and environments. So, we proposed a data augmentation and generation method for robot manipulation tasks to advance reinforced learning from toy tasks to complex tasks and to create millions of high-fidelity visual and tactile data for both long-term planning and sophisticated low-level control.
Overview of Interactive Simulation Platform: Playground.
Research 1 : Multi-scenarios Playground for Robots
We provide the simulation platform for robots’ tasks under 8 different scenarios. The scenarios contain of Nearby town, Store, Garage, Kitchen, Living room, Storage room, Bedroom, Vineyard, Orchard. Each secne contains:
Fully defined interactive objects;
Furnitures and obstacles with accurate colliders;
Visual data with high fidelity.