Abstract: Local obstacle avoidance is critical for mobile robot
navigation. It is a challenging task to ensure path optimality and
safety in cluttered environments. We proposed an Environment
Aware Dynamic Window Approach in this paper to cope with
the issue. The method integrates environment characterization into
Dynamic Window Approach (DWA). Two strategies are proposed
in order to achieve the integration. The local goal strategy guides
the robot to move through openings before approaching the final
goal, which solves the local minima problem in DWA. The adaptive
control strategy endows the robot to adjust its state according
to the environment, which addresses path safety compared with
DWA. Besides, the evaluation shows that the path generated from
the proposed algorithm is safer and smoother compared with
state-of-the-art algorithms.
Abstract: In this work, we suggested a new approach for the
control of a mobile robot capable of being a building block of an
intelligent agent. This approach includes obstacle avoidance and goal
tracking implemented as two different sliding mode controllers. A
geometry based behavior arbitration is proposed for fusing the two
outputs. Proposed structure is tested on simulations and real robot.
Results have confirmed the high performance of the method.