Autonomous Street Crossing with City Navigation Robots

城市导航机器人自主过马路

• 批准号: 406258464
• 负责人: Professor Dr. Wolfram Burgard
• 金额: --
• 依托单位: Department Engineering
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/406258464?language=en
• 关键词: Autonomous; Street; Crossing; City; Navigation

Autonomous urban navigation poses a variety of difficult problems. Among them, one of the most challenging ones is that of autonomously crossing streets. While the problem of crossing streets with city navigating vehicles has been studied intensively in the past, the majority of recent work focused on the specific task of crossing signalized crosswalks or required the assistance of humans. In this project, we will develop a completely autonomous approach for crossing streets that allows a robot to cross a street even when there is no crosswalk nor a signalized pedestrian crossing. To achieve this, we will follow multimodal approaches based on images, lidar and sound data for the identification of crossing opportunities and the tracking of other traffic participants. In addition, we will employ inverse reinforcement learning to infer crossing policies from observations of human street crossing activities.

自主城市导航带来了各种各样的难题。其中，最具挑战性的是自动过马路。虽然城市导航车辆过街问题在过去已经被深入研究，但最近的大部分工作都集中在过信号控制人行横道或需要人类协助的特定任务上。在这个项目中，我们将开发一种完全自主的过街方法，即使没有人行横道或信号灯的人行横道，机器人也可以过街。为了实现这一目标，我们将遵循基于图像、激光雷达和声音数据的多模式方法，以识别交叉路口的机会并跟踪其他交通参与者。此外，我们将采用反向强化学习来从对人类过街活动的观察中推断过街策略。