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Bringing Belief Space Planning to Physical Systems
Sampling based deterministic motion planning has shown great success in the past. However, as we progress towards more realistic modeling and planning for robotic systems, we need to account for uncertainties in our systems. Uncertainties mainly arise from: 1. Sensing or measurement noise (also called observation noise) i.e. sensors do not give perfect measurements, instead […]