.png){kind=icon}
Return
Obstacle Avoidance Using Multiobjective Optimization and a Dynamic Obstacle Manager
.png){kind=icon}
PRE
AI
DOI：10.1109/JOE.2019.2896504.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper describes a set of software modules and algorithms for obstacle avoidance. The approach described here is designed to work in conjunction with any path planning method that generates a viable sequence of waypoints, with obstacle avoidance regarded as a local deviation of the planned path of points. The helm architecture used here will temporarily spawn a new obstacle avoidance behavior for each near detected obstacle, and generate a maneuvering objective function to avoid the obstacle. Once the vehicle passes the obstacle, the helm deletes the behavior and frees its memory space. The helm, obstacle manager, and obstacle avoidance behavior are described here. This software arrangement was used by the MIT 2014 RobotX team, and will be included in the next software release of the open source MOOS-IvP marine autonomy project.
Keywords:
Autonomous systems
intelligent robots
mobile agents unmanned autonomous vehicles
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.3
Papers:
2.6K
Citations:
7.4K
Organization
No organization information available
Cited Papers
ShareSaveDistributed Information Fusion in Multistatic Sensor Networks for Underwater Surveillance.png)
IEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
ShareSave
ShareSaveShareSave
View more