Mini bot 3D: A ROS based Gazebo Simulation

TL;DR

This paper reviews recent ROS-based Gazebo simulation approaches for autonomous mobile robot navigation, focusing on adaptive SLAM, odometry, and localization techniques suitable for indoor and outdoor environments.

Contribution

It provides a comprehensive overview of state-of-the-art adaptive onboard navigation methods using Gazebo and ROS, emphasizing dynamic sensor uncertainty and scene adaptability.

Findings

Survey of recent adaptive navigation approaches

Insights into sensor fusion and environment transition techniques

Guidance for roboticists on autonomous SLAM implementation

Abstract

The recent adoption of the Robot Operating System (ROS) as a software standard in robotics has contributed to novel solutions for several problems on the area. One such problem is known as Simultaneous Localization and Mapping (SLAM) with autonomous navigation, for which a number of algorithms from different classes are available as ROS packages ready to be used on any compatible robot. Many anticipated applications of autonomous mobile robots require for them to navigate in diverse complex environments without support from exterior infrastructures. To perform this on-board navigation, the robot must make use of the available sensor technologies and fuse the most reliable data respective to the present environment in an adaptive manner and optimize the algorithm parameters prior to the actual implementation to reduce the workaround time. This paper will review recent efforts to develop onboard navigation systems which can seamlessly transition between outdoor and indoor environments and different terrains seamlessly using Gazebo simulator with ROS integration. The methodologies surveyed include SLAM, Odometry and Localisation. An overview of the state-of-the-art is provided with a focus on approaches which are adaptive to dynamic sensor uncertainty, dynamic objects and dynamic scenes. The experiences reported on this work should provide insight for roboticists seeking an Autonomous SLAM solution for indoor applications.