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

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...

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Published in:	IEEE robotics and automation letters Vol. 5; no. 2; pp. 713 - 720
Main Authors:	Xia, Fei, Shen, William B., Li, Chengshu, Kasimbeg, Priya, Tchapmi, Micael Edmond, Toshev, Alexander, Martin-Martin, Roberto, Savarese, Silvio
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Benchmark testing Benchmarks deep learning in robotics and automation Engines Indoor environments Interactive control Learning Measurement mobile manipulation Navigation Robotics Robots Solid modeling Task analysis Visual-based navigation
ISSN:	2377-3766, 2377-3766
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Abstract	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.
AbstractList	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. 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 available 1 1 [Online]. Available: https://sites.google.com/view/interactivegibsonenv . 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.
Author	Xia, Fei Martin-Martin, Roberto Kasimbeg, Priya Savarese, Silvio Toshev, Alexander Shen, William B. Tchapmi, Micael Edmond Li, Chengshu
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Snippet	We present Interactive Gibson Benchmark, the first comprehensive benchmark for training and evaluating Interactive Navigation solutions. Interactive Navigation... We present Interactive Gibson Benchmark , the first comprehensive benchmark for training and evaluating Interactive Navigation solutions. Interactive...
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SubjectTerms	Benchmark testing Benchmarks deep learning in robotics and automation Engines Indoor environments Interactive control Learning Measurement mobile manipulation Navigation Robotics Robots Solid modeling Task analysis Visual-based navigation
Title	Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments
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