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

被引:80
|
作者
Xia, Fei [1 ]
Shen, William B. [1 ]
Li, Chengshu [1 ]
Kasimbeg, Priya [1 ]
Tchapmi, Micael Edmond [1 ]
Toshev, Alexander [2 ]
Martin-Martin, Roberto [1 ]
Savarese, Silvio [1 ]
机构
[1] Stanford Univ, SAIL, Stanford, CA 94305 USA
[2] Google, Robot, Mountain View, CA 94043 USA
关键词
Visual-based navigation; deep learning in robotics and automation; mobile manipulation; ROBOTICS;
D O I
10.1109/LRA.2020.2965078
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
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) 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.
引用
收藏
页码:713 / 720
页数:8
相关论文
共 50 条
  • [1] Transformer Memory for Interactive Visual Navigation in Cluttered Environments
    Li, Weiyuan
    Hong, Ruoxin
    Shen, Jiwei
    Yuan, Liang
    Lu, Yue
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2023, 8 (03) : 1731 - 1738
  • [2] IDEBench: A Benchmark for Interactive Data Exploration
    Eichmann, Philipp
    Zgraggen, Emanuel
    Binnig, Carsten
    Kraska, Tim
    [J]. SIGMOD'20: PROCEEDINGS OF THE 2020 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2020, : 1555 - 1569
  • [3] Interactive benchmark for planning algorithms on the web
    Piccinocchi, S
    Ceccarelli, M
    Piloni, F
    Bicchi, A
    [J]. 1997 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION - PROCEEDINGS, VOLS 1-4, 1997, : 399 - 404
  • [4] Exploratory analysis of benchmark experiments an interactive approach
    Eugster, Manuel J. A.
    Leisch, Friedrich
    [J]. COMPUTATIONAL STATISTICS, 2011, 26 (04) : 699 - 710
  • [5] The LDBC Social Network Benchmark: Interactive Workload
    Erling, Orri
    Averbuch, Alex
    Larriba-Pey, Josep
    Chafi, Hassan
    Gubichev, Andrey
    Prat, Arnau
    Minh-Duc Pham
    Boncz, Peter
    [J]. SIGMOD'15: PROCEEDINGS OF THE 2015 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2015, : 619 - 630
  • [6] Exploratory analysis of benchmark experiments an interactive approach
    Manuel J. A. Eugster
    Friedrich Leisch
    [J]. Computational Statistics, 2011, 26 : 699 - 710
  • [7] Learning Cross Dimension Scene Representation for Interactive Navigation Agents in Obstacle-Cluttered Environments
    Sang, Hongrui
    Jiang, Rong
    Li, Xin
    Wang, Zhipeng
    Zhou, Yanmin
    He, Bin
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2024, 9 (07): : 6264 - 6271
  • [8] Probabilistic Interactive Segmentation for Anthropomorphic Robots in Cluttered Environments
    van Hoof, Herke
    Kroemer, Oliver
    Peters, Jan
    [J]. 2013 13TH IEEE-RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS), 2013, : 169 - 176
  • [9] A Benchmark for Multi-Robot Planning in Realistic, Complex and Cluttered Environments
    Schaefer, Simon
    Palinieri, Luigi
    Heuer, Lukas
    Dillmann, Ruediger
    Koenig, Sven
    Kleiner, Alexander
    [J]. 2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2023), 2023, : 9231 - 9237
  • [10] BG: A scalable benchmark for interactive social networking actions
    Alabdulkarim, Yazeed
    Barahmand, Sumita
    Ghandeharizadeh, Shahram
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 85 : 29 - 38