Peter Stone's Selected Publications

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Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots

Shiqi Zhang, Dongcai Lu, Xiaoping Chen, and Peter Stone. Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2016.

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Abstract

In recent years, many different types of intelligent mobile robots have been developed in research and industrial labs. Although there are significant differences in both hardware and software over these robots, many of them share a common set of AI capabilities, e.g., planning, learning, vision and natural language processing. At the same time, almost all of them are equipped with traditional robotic capabilities such as mapping, localization, and navigation. However, to date it has been difficult to compare and contrast their capabilities in any controlled way. The main goal of the Robot Scavenger Hunt is to provide a standardized framework that includes a set of standardized tasks for evaluating the AI and robotic capabilities of medium-sized intelligent mobile robots. Compared to existing benchmarks, e.g., RoboCup@Home1, Robot Scavenger Hunt aims at evaluations in larger spaces (multi-floor buildings vs. rooms) over longer periods of time (hours vs. minutes) while interacting with real human residents.

BibTeX Entry

@InProceedings{IJCAI16-szhang,
  author = {Shiqi Zhang and Dongcai Lu and Xiaoping Chen and Peter Stone},
  title = {Robot Scavenger Hunt: A Standardized Framework for Evaluating
  Intelligent Mobile Robots},
  booktitle = {Proceedings of the International Joint Conference on Artificial
  Intelligence (IJCAI)},
  location = {New York City, USA},
  month = {July},
  year = {2016},
  abstract = {In recent years, many different types of intelligent mobile robots
    have been developed in research and industrial labs.  Although there are
    significant differences in both hardware and software over these robots,
    many of them share a common set of AI capabilities, e.g., planning,
    learning, vision and natural language processing. At the same time, almost
    all of them are equipped with traditional robotic capabilities such as
    mapping, localization, and navigation. However, to date it has been
    difficult to compare and contrast their capabilities in any controlled way.
    The main goal of the Robot Scavenger Hunt is to provide a standardized
    framework that includes a set of standardized tasks for evaluating the AI
    and robotic capabilities of medium-sized intelligent mobile robots. Compared
    to existing benchmarks, e.g., RoboCup@Home1, Robot Scavenger Hunt aims at
    evaluations in larger spaces (multi-floor buildings vs. rooms) over longer
    periods of time (hours vs.  minutes) while interacting with real human
    residents.
  },
}

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