As autonomous driving technology is getting more and more mature today, autonomous delivery companies like Starship, Marble, and Nuro has been making progress in the tests of their autonomous delivery robots. While simulations and simulators are very important for the final product landing of the autonomous delivery robots since the autonomous delivery robots need to navigate on the sidewalk, campus, and other urban scenarios, where the simulations can avoid real damage to pedestrians and properties in the real world caused by any algorithm failures and programming errors and thus accelerate the whole developing procedure and cut down the cost. In this case, this study proposes an open-source simulator based on our autonomous delivery robot ZebraT to accelerate the research on autonomous delivery. The simulator developing procedure is illustrated step by step. What is more, the applications on the simulator that we are working on are also introduced, which includes autonomous navigation in the simulated urban environment, cooperation between an autonomous vehicle and an autonomous delivery robot, and reinforcement learning practice on the task training in the simulator. We have published the proposed simulator in Github.
翻译:随着自主驾驶技术的日益成熟,诸如Starship、Marble和Nuro等自主提供公司在自动交付机器人的测试方面不断取得进展。虽然模拟和模拟器对于自动交付机器人的最终产品着陆非常重要,因为自动交付机器人需要在人行道、校园和其他城市情景上导航,而模拟可以避免任何算法故障和编程错误对现实世界行人和财产造成实际损害,从而加快整个开发程序并降低成本。在这种情况下,本研究提议以我们的自动交付机器人ZebraT为基础,开发开放源模拟器,以加速自动交付研究。模拟器的开发程序是一步一步地展示的。此外,我们正在开发的模拟器上的应用也在引入,其中包括模拟城市环境中的自主导航,自动车辆与自动交付机器人之间的合作,以及在模拟器中强化任务培训的学习实践。我们已在Github公布了拟议的模拟器模拟器。