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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Vydáno v:IEEE robotics and automation letters Ročník 5; číslo 2; s. 713 - 720
Hlavní autoři: Xia, Fei, Shen, William B., Li, Chengshu, Kasimbeg, Priya, Tchapmi, Micael Edmond, Toshev, Alexander, Martin-Martin, Roberto, Savarese, Silvio
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.04.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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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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