Autonomous navigation in dynamic social environments using multi-policy decision making

Dhanvin Mehta, Gonzalo Ferrer, Edwin Olson

Результат исследований: Глава в книге, отчете, сборнике статейМатериалы для конференциирецензирование

40 Цитирования (Scopus)

Аннотация

In dynamic environments crowded with people, robot motion planning becomes difficult due to the complex and tightly-coupled interactions between agents. Trajectory planning methods, supported by models of typical human behavior and personal space, often produce reasonable behavior. However, they do not account for the future closedloop interactions of other agents with the trajectory being constructed. As a consequence, the trajectories are unable to anticipate cooperative interactions (such as a human yielding), or adverse interactions (such as the robot blocking the way). In this paper, we propose a new method for navigation amongst pedestrians in which the trajectory of the robot is not explicitly planned, but instead, a planning process selects one of a set of closed-loop behaviors whose utility can be predicted through forward simulation. In particular, we extend Multi-Policy Decision Making (MPDM) [1] to this domain using the closed-loop behaviors Go-Solo, Follow-other, and Stop. By dynamically switching between these policies, we show that we can improve the performance of the robot as measured by utility functions that reward task completion and penalize inconvenience to other agents. Our evaluation includes extensive results in simulation and real-world experiments.

Язык оригиналаАнглийский
Название основной публикацииIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы1190-1197
Число страниц8
ISBN (электронное издание)9781509037629
DOI
СостояниеОпубликовано - 28 нояб. 2016
Опубликовано для внешнего пользованияДа
Событие2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Республика Корея
Продолжительность: 9 окт. 201614 окт. 2016

Серия публикаций

НазваниеIEEE International Conference on Intelligent Robots and Systems
Том2016-November
ISSN (печатное издание)2153-0858
ISSN (электронное издание)2153-0866

Конференция

Конференция2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Страна/TерриторияРеспублика Корея
ГородDaejeon
Период9/10/1614/10/16

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