Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified \textit{planning model} of the system. The plan is tracked by the system, represented by a more realistic, higher-dimensional \textit{tracking model}. We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton-Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs.
翻译:实时、有保障的安全轨道规划对于在未知环境中的导航至关重要。 然而, 实时导航算法通常会牺牲计算速度的稳健性。 或者, 安全的轨道规划往往会过于频繁地进行实时重新规划。 我们提议采用Fastrack、 Fastrack、 Fast and Safety track, 这个框架既能实现实时再规划,又能保证安全。 在这个框架内, 实时计算的方法是允许任何轨道规划员使用系统简化的\ textit{planalit{production 模式。 该计划由系统跟踪, 由更现实的、 更高维度的 \ textit{ tracking model} 来代表。 我们预估测了由于两种模型之间的不匹配和外部干扰而形成的追踪错误。 我们还获得了用于在 TEB 内停留的对应跟踪控制器。 预算不需要事先对环境的了解。 我们用汉密尔顿- Jacobi 的可达标度来进行计算。 我们用三个不同的跟踪规划模型来演示法斯特拉克。