Abstract:
Active SLAM poses the challenge for an
autonomous robot to plan efficient paths simultaneous to the
SLAM process. The uncertainties of the robot, map and sensor
measurements, and the dynamic and motion constraints need to
be considered in the planning process. In this paper, the active
SLAM problem is formulated as an optimal trajectory planning
problem. A novel technique is introduced that utilises an
attractor combined with local planning strategies such as Model
Predictive Control (a.k.a. Receding Horizon) to solve this
problem. An attractor provides high level task intentions and
incorporates global information about the environment for the
local planner, thereby eliminating the need for costly global
planning with longer horizons. It is demonstrated that trajectory
planning with an attractor results in improved performance over
systems that have local planning alone.
