iGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenes
Bokui Shen, Fei Xia, Chengshu Li, Roberto Mart\'in-Mart\'in, Linxi, Fan, Guanzhi Wang, Claudia P\'erez-D'Arpino, Shyamal Buch, Sanjana, Srivastava, Lyne P. Tchapmi, Micael E. Tchapmi, Kent Vainio, Josiah Wong, Li, Fei-Fei, Silvio Savarese

TL;DR
iGibson 1.0 is a comprehensive simulation platform with realistic scenes and tools for developing and training robots in interactive tasks, supporting visual perception, motion planning, and imitation learning.
Contribution
The paper introduces iGibson 1.0, a new simulation environment with realistic scenes, sensor generation, domain randomization, and integrated motion planning for robotic interactive tasks.
Findings
Enables learning of visual representations for manipulation tasks.
Facilitates generalization of navigation agents.
Supports efficient imitation learning of manipulation behaviors.
Abstract
We present iGibson 1.0, a novel simulation environment to develop robotic solutions for interactive tasks in large-scale realistic scenes. Our environment contains 15 fully interactive home-sized scenes with 108 rooms populated with rigid and articulated objects. The scenes are replicas of real-world homes, with distribution and the layout of objects aligned to those of the real world. iGibson 1.0 integrates several key features to facilitate the study of interactive tasks: i) generation of high-quality virtual sensor signals (RGB, depth, segmentation, LiDAR, flow and so on), ii) domain randomization to change the materials of the objects (both visual and physical) and/or their shapes, iii) integrated sampling-based motion planners to generate collision-free trajectories for robot bases and arms, and iv) intuitive human-iGibson interface that enables efficient collection of human…
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Taxonomy
TopicsRobot Manipulation and Learning · Human Pose and Action Recognition · Robotic Path Planning Algorithms
