Now assume that there is a continuum of stages. Most of the components of Section 11.4.1 remain the same. The spaces , , , , and remain the same. The sensor mapping also remains the same. The main difference occurs in the state transition equation because the effect of nature must be expressed in terms of velocities. This was already introduced in Section 10.6. In that context, there was only uncertainty in predictability. In the current context there may be uncertainties in both predictability and in sensing the current state.
For the discrete-stage case, the history I-states were based on action and observation sequences. For the continuous-time case, the history instead becomes a function of time. As defined in Section 7.1.1, let denote a time interval, which may be bounded or unbounded. Let be called the observation history up to time . Similarly, let and be called the action history and state history, respectively, up to time .
Thus, the three kinds of sensor mappings in the continuous-time case are as follows:
If and are combined with the initial condition , the history I-state at time is obtained as
(11.53) |
A continuous-time version of the cost functional in Formulation 11.1 can be given to evaluate the execution of a plan. Let denote a cost functional that may be applied to any state-action history to yield
(11.55) |
Steven M LaValle 2020-08-14