图 书 馆
从线性可解最优控制到轨迹优化（希望）返回From linearly-solvable optimal control to trajectory optimization, and (hopefully) back |
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| 课程网址: | http://videolectures.net/cyberstat2012_todorov_optimal_control/ |
| 主讲教师: | Emanuel Todorov |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2012-10-16 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We have identified a general class of stochastic optimal control problems which are inherently linear, in the sense that the exponentiated optimal value function satisfies a linear equation. These problems have a number of unique properties which enable more efficient numerical methods than generic formulations. However, after several attempts to go beyond the simple numerical examples characteristic of this literature and scale to real-world problems (particularly in robotics), we realized that the curse of dimensionality is still a curse. We then took a detour, and developed trajectory optimization methods that can synthesize remarkably complex behaviors fully automatically. Thanks to the parallel processing capabilities of modern computers, some of these methods work in real time in model-predictive-control (MPC) mode, giving rise to implicitly defined feedback control laws. But not all problems can be solved in this way, and furthermore it would be nice to somehow re-use the local solutions that MPC generates. The next step is to combine the strengths of these two approaches: using trajectory optimization to identify the regions of state space where the optimally-controlled stochastic system is likely to spend its time, and then applying linearly-solvable optimal control restricted to these regions. |
| 关 键 词: | 线性方程; 随机最优控制; 机器人技术 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-29：cxin |
| 阅读次数: | 90 |