|
RADHAR - 适应于人类的机器人
RADHAR - Robotic Adaptation to Humans Adapting to Robots |
|
| |
| 课程网址: |
http://videolectures.net/cogsys2012_demeester_adaptation/
|
| 主讲教师: |
Eric Demeester
|
| 开课单位: |
鲁汶大学
|
| 开课时间: |
2013-03-14
|
| 课程语种: |
英语
|
| 中文简介: |
RADHAR将开发一个包括环境感知、驾驶员感知和建模以及机器人决策在内的驾驶辅助系统。RADHAR提出了一种框架，通过估计机器人应该执行的轨迹来无缝地融合来自环境感知和驾驶员转向信号的固有不确定信息，并且采用该融合信息用于安全导航，其自主性水平根据用户的能力和愿望进行调整。这需要机器人终生、无监督但安全的学习。因此，两个学习系统（机器人和用户）之间的持续交互将会出现，因此机器人适应人类适应机器人（RADHAR）。该框架将在一个机器人轮椅平台上演示，该平台在具有日常对象的日常环境中导航。RADHAR目标作为主要的科学成果：结合激光扫描仪和视觉与地形遍历性分析的在线3D感知；融合环境和用户感知以及安全机器人导航的新范例。
|
| 课程简介: |
RADHAR will develop a driving assistance system involving environment perception, driver perception and modelling, and robot decision making. RADHAR proposes a framework to seamlessly fuse the inherently uncertain information from both environment perception and the driver's steering signals by estimating the trajectory the robot should execute, and to adopt this fused information for safe navigation with a level of autonomy adjusted to the user's capabilities and desires. This requires lifelong, unsupervised but safe learning by the robot. As a consequence, a continuous interaction between two learning systems (the robot and the user) will emerge, hence Robotic ADaptation to Humans Adapting to Robots (RADHAR). The framework will be demonstrated on a robotic wheelchair platform that navigates in an everyday environment with everyday objects. RADHAR targets as main scientific outcomes: online 3D perception combining laser scanners and vision with traversability analysis of the terrain; novel paradigm for fusing environment and user perception and for safe robot navigation.
|
| 关 键 词: |
驾驶辅助系统; 环境感知; 驱动感知; 机器人决策
|
| 课程来源: |
视频讲座网
|
| 最后编审: |
2019-11-11：chenxin
|
| 阅读次数: |
150
|
|
图 书 馆