A Robotic Software Framework for Autonomous Navigation in Unknown Environment

Abstract

Autonomously navigating a robot in an unknown scene comprises tasks such as mapping and localization from the percepts via sensors, safe motion-planning under partial knowledge of the scene, and finally, plan execution using the available motion primitives of the robot. Though many software systems are available for these sub-tasks, there is a lack of integrated software that support autonomous navigation. In this paper, we present an integrated software framework comprising of simultaneous localization and mapping module using visual odometry, a motion-planning module based on constraint-solving, and a plan-execution module particularly designed for a lizard-inspired quadruped robot. To demonstrate its efficacy, we present a number of navigation tasks to the software framework in various indoor simulation settings together with a model of the lizard-inspired quadruped robot and show the results. © 2021 IEEE.