Adaptive Landmark-Based Navigation System Using Learning Techniques

Abstract. The goal-directed navigational ability of animals is an essen-tial prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance naviga-tion, they exploit environmental features, like landmarks, to guide them towards their goal. Inspired by this, we develop an adaptive landmark-based navigation system based on sequential reinforcement learning. In addition, correlation-based learning is also integrated into the system to improve learning performance. The proposed system has been applied to simulated simple wheeled and more complex hexapod robots. As a re-sult, it allows the robots to successfully learn to navigate to distal goals in complex environments