This paper is the second part of the authors' contribution on the topic of safe navigation for indoor mobile robots. It presents a new solution to the exploration, self-localization and map building problem taking advantage of the sensor-based navigation framework presented in Part I: A Sensor-Based Navigation Framework. The model of the indoor environment is structured as a hybrid representation, both topological and geometrical, which is incrementally built during the exploration task. The topological aspect of the model captures the connectivity and accessibility of the different places in the environment, and the geometrical model holds up an accurate robot localization and map building method. To overcome the problem of drift inherited to the odometry when the robot navigates in large-scale environments, a new dead-reckoning method is proposed combining laser readings and feedback control inputs. Embedding the selflocalization and map building problem in a sensor-based navigation framework improves both the quality and the robustness of the representation built during the exploration phase and authorizes a further use to achieve safe navigation tasks successfully. Experiments are shown which confirm the interests of the proposed methodology. KEY WORDS-concurrent localization and mapping, sensor-based navigation, hybrid topological and metrical representation, robust motion estimation
Victorino et al. REF proposed a new approach for indoor environments with a topological representation of the robot path.
Safe Navigation for Indoor Mobile Robots. Part II: Exploration, Self-Localization and Map Building
The International Journal of Robotics Research
Mathematics Computer Science