Risk-aware Spatio-temporal Logic Planning in Gaussian Belief Spaces
Matti Vahs,Christian Pek,Jana Tumova,Matti Vahs,Christian Pek,Jana Tumova
In many real-world robotic scenarios, we cannot assume exact knowledge about a robot's state due to unmodeled dynamics or noisy sensors. Planning in belief space addresses this problem by tightly coupling perception and planning modules to obtain trajectories that take into account the environment's stochasticity. However, existing works are often limited to tasks such as the classic reach-avoid p...
