Details

Autor(en) / Beteiligte

• Xia, Fei
• Shen, William B.
• Li, Chengshu
• Kasimbeg, Priya
• Tchapmi, Micael Edmond
• Toshev, Alexander
• Martin-Martin, Roberto
• Savarese, Silvio

Titel

Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments

Ist Teil von

• IEEE robotics and automation letters, 2020-04, Vol.5 (2), p.713-720

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2020

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• We present Interactive Gibson Benchmark, the first comprehensive benchmark for training and evaluating Interactive Navigation solutions. Interactive Navigation tasks are robot navigation problems where physical interaction with objects (e.g., pushing) is allowed and even encouraged to reach the goal. Our benchmark comprises two novel elements: 1) a new experimental simulated environment, the Interactive Gibson Environment, that generate photo-realistic images of indoor scenes and simulates realistic physical interactions of robots and common objects found in these scenes; 2) the Interactive Navigation Score, a novel metric to study the interplay between navigation and physical interaction of Interactive Navigation solutions. We present and evaluate multiple learning-based baselines in Interactive Gibson Benchmark, and provide insights into regimes of navigation with different trade-offs between navigation, path efficiency and disturbance of surrounding objects. We make our benchmark publicly available1 and encourage researchers from related robotics disciplines (e.g., planning, learning, control) to propose, evaluate, and compare their Interactive Navigation solutions in Interactive Gibson Benchmark.