Abstract:
This paper provides a solution to the optimal
trajectory planning problem in target localisation for multiple
heterogeneous robots with bearing-only sensors. The objective
here is to find robot trajectories that maximise the accuracy of
the locations of the targets at a prescribed terminal time. The
trajectory planning is formulated as an optimal control problem
for a nonlinear system with a gradually identified model and then
solved using nonlinear Model Predictive Control (MPC). The
solution to the MPC optimisation problem is computed through
Exhaustive Expansion Tree Search (EETS) plus Sequential
Quadratic Programming (SQP). Simulations were conducted
using the proposed methods. Results show that EETS alone
performs considerably faster than EETS+SQP with only minor
differences in information gain, and that a centralised approach
outperforms a decentralised one in terms of information gain.
We show that a centralised EETS provides a near optimal
solution. We also demonstrate the significance of using a matrix
to represent the information gathered.
