Full-stack S-DOVS: Autonomous Navigation in Complete Real-World Dynamic Scenarios

被引：0

作者：

Martinez, Diego ^{[1
]}

Riazuelo, Luis ^{[1
]}

Montano, Luis ^{[1
]}

机构：

[1] Univ Zaragoza, Engn Res Inst Aragon I3A, Zaragoza, Spain

来源：

ROBOT2022: FIFTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 2 | 2023年 / 590卷

关键词：

Autonomous navigation; Dynamic environment; Obstacle avoidance;

D O I：

10.1007/978-3-031-21062-4_2

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Autonomous navigation in dynamic environments is a nowadays unsolved challenge. Several approaches have been proposed to solve it, but they either have a low success rate, do not consider robot kinodynamic constraints or are not able to navigate through big scenarios where the known map information is needed. In this work, a previously existing planner, the Strategy-based Dynamic Object Velocity Space, S-DOVS, is modified and adapted to be included in a full navigation stack, with a localization system, an obstacle tracker and a global planner. The result is a system that is able to navigate successfully in real-world scenarios, where it may face complex challenges as dynamic obstacles or replanning. The final work is exhaustively tested in simulation and in a ground robot.

引用

页码：14 / 25

页数：12

共 29 条

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