A Model for Verifiable Grounding and Execution of Complex Natural Language Instructions

被引：0
|
作者：
Boteanu, Adrian [1 ]
Howard, Thomas [2 ]
Arkin, Jacob [2 ]
Kress-Gazit, Hadas [1 ]
机构：
[1] Cornell Univ, Sibley Sch Mech & Aerosp Engn, Ithaca, NY 14853 USA
[2] Univ Rochester, Hajim Sch Engn & Appl Sci, 601 Elmwood Ave, Rochester, NY 14627 USA
来源：
2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016) | 2016年
基金：
美国国家科学基金会;
关键词：
SCHEMAS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Current methods of grounding natural language instructions do not include reactive or temporal components, making these methods unsuitable for instructions describing tasks as sets of conditional instructions. We introduce the Verifiable Distributed Correspondence Graph (V-DCG) model, which enables the validation of natural language instructions by using Linear Temporal Logic (LTL) specifications together with physical world groundings. We demonstrate the V-DCG model on a physical robot and provide examples of the output our system produces for natural language instructions.
引用
收藏
页码：2649 / 2654
页数：6
相关论文
共 50 条
  • [41] OCL as the query language for UML model execution
    Habela, Piotr
    Kaczmarski, Krzysztof
    Stencel, Krzysztof
    Subieta, Kazimierz
    COMPUTATIONAL SCIENCE - ICCS 2008, PT 3, 2008, 5103 : 311 - 320
  • [42] Hierarchical Decision Making by Generating and Following Natural Language Instructions
    Hu, Hengyuan
    Yarats, Denis
    Gong, Qucheng
    Tian, Yuandong
    Lewis, Mike
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 2019, 32
  • [43] Spatial References and Perspective in Natural Language Instructions for Collaborative Manipulation
    Li, Shen
    Scalise, Rosario
    Admoni, Henny
    Rosenthal, Stephanie
    Srinivasa, Siddhartha S.
    2016 25TH IEEE INTERNATIONAL SYMPOSIUM ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (RO-MAN), 2016, : 44 - 51
  • [44] Teaching Robots New Actions through Natural Language Instructions
    She, Lanbo
    Cheng, Yu
    Chai, Joyce Y.
    Jia, Yunyi
    Yang, Shaohua
    Xi, Ning
    2014 23RD IEEE INTERNATIONAL SYMPOSIUM ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (IEEE RO-MAN), 2014, : 868 - 873
  • [45] Natural language instructions induce compositional generalization in networks of neurons
    Riveland, Reidar
    Pouget, Alexandre
    NATURE NEUROSCIENCE, 2024, 27 (05) : 988 - 999
  • [46] Converting natural language route instructions into robot executable procedures
    Lauria, S
    Bugmann, G
    Kyriacou, T
    Bos, J
    Klein, E
    IEEE ROMAN 2002, PROCEEDINGS, 2002, : 223 - 228
  • [47] Natural language instructions for human-robot collaborative manipulation
    Scalise, Rosario
    Li, Shen
    Admoni, Henny
    Rosenthal, Stephanie
    Srinivasa, Siddhartha S.
    INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2018, 37 (06): : 558 - 565
  • [48] Robust comprehension of natural language instructions by a domestic service robot
    Kobori, Takahiro
    Nakamura, Tomoaki
    Nakano, Mikio
    Nagai, Takayuki
    Iwahashi, Naoto
    Funakoshi, Kotaro
    Kaneko, Masahide
    ADVANCED ROBOTICS, 2016, 30 (24) : 1530 - 1543
  • [49] COMPLEX NATURAL SYSTEMS FOR LANGUAGE
    Dziubalsk-Kolaczyk, Ktarzyna
    Kretzschmar Jr, William A.
    ROCZNIKI HUMANISTYCZNE, 2023, 71 (06): : 65 - 101
  • [50] Language as a Complex Natural System
    Barcelo-Coblijn, Lluis
    LLENGUA SOCIETAT I COMUNICACIO, 2013, (11): : 34 - 41
12345