基于物理引擎的智能汽车仿真调试环境

Feng Luo, Chu Liu, Zechang Sun
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引用次数: 13

摘要

为了提高嵌入式智能汽车系统的开发效率,取代传统嵌入式系统低效的调试方法,开发了一种能够在白色路线上检测黑色轨迹,实现快速自动驾驶的智能汽车仿真调试环境。该系统集成了OpenGL图形引擎,构建模拟路线和车辆,执行整个场景,并在屏幕上显示物体。将ODE物理引擎引入到环境中进行刚体动力学仿真,实现车辆的驱动和与其他场景对象的交互。算法和其他用户自定义函数在PC上编译成算法库,可直接通过仿真环境进行调试,简化了代码移植过程。使用这种环境,将更方便地保证智能汽车软件的稳定性和鲁棒性。同时,可以生成高性能的软件代码,实现精确的转向控制和安全驾驶,使智能车辆能够在给定的任何路线上高速稳定运行。测试结果表明,该智能汽车仿真调试环境确实能够显著提高开发效率,加快开发进度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Vehicle Simulation and Debugging Environment Based on Physics Engine
In order to improve the development efficiency of the embedded intelligent vehicle system and replace the inefficient traditional embedded system debugging method, a simulation and debugging environment is developed for intelligent vehicles which are able to detect black tracks on white routes and realize fast automatic driving. OpenGL graphics engine is integrated in this system, which constructs simulated routes and vehicles, performs the whole scene and displays objects on the screen. ODE physics engine is introduced to the environment for the simulation of rigid body dynamics, and makes vehicle drive and interact with other scene objects. Algorithm and other user defined functions are compiled into an algorithm library on the PC and can be debugged directly by the simulation environment, which eases the code transplant process. By using this environment, it will be more convenient to guarantee the stability and robustness of the software of intelligent vehicles. In the meantime, high performance software code can be produced for precise steer control and safe driving, and the intelligent vehicles are able to run stably on any provided course at a high speed. Test results show that the intelligent vehicle simulation and debugging environment could actually improve the development efficiency and speed up the development progress significantly.
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