14 May 2025

Autonomous Robotics Development in Robot Operating System (ROS) 2 Humble

Abstract: This report presents a novel Robot Operating System (ROS) 2–based simulation framework designed to facilitate the development and testing of an autonomous navigation stack. Elements of the navigation stack, including lidar odometry, simultaneous localization and mapping (SLAM), and frontier exploration, are discussed in detail. The key features of the navigation stack include real-time performance and scalable architecture. The simulation results were applied to a physical robot. As a result, the physical robot was able to autonomously map the interior of a building and to generate 2D occupancy and 3D point clouds of the environment.

14 May 2025

Robot Operating System Innovations in Autonomous Navigation

Abstract: This report presents the results of simulations conducted in preparation for the 2024 Maneuver Support and Protection Integration Experiments (MSPIX) demonstration. The study aimed to develop and test a system for autonomous navigation in complex environments using advanced algorithms to enable the robot to avoid obstacles and navigate safely and efficiently. The report describes the methodology used to develop and test the autonomous navigation system, including the use of simulation, to evaluate its performance. The results of the simulation tests are presented to highlight the effectiveness of the navigation solution.

29 Aug 2023

Unmanned Ground Vehicle (UGV) Full Coverage Planning with Negative Obstacles

Abstract: We explored approaches that offer full coverage path planning while simultaneously avoiding negative obstacles. These approaches are specific to unmanned ground vehicles (UGVs), which need to constantly interact with a traversable ground surface. We tested multiple potential solutions in simulation, and the results are presented herein. Full coverage path planner (FCPP) approaches were evaluated based on their ability to discretize their paths, use waypoints effectively, and be easily integrated with our current robot platform. For negative obstacles, we explored approaches that will integrate with our current navigation stack. The preferred solution will allow for teleoperation, waypoint navigation, and full autonomy while avoiding positive and negative obstacles

20 Sep 2021

Autonomous Navigation and Mapping in a Simulated Environment

Abstract: Unknown Environment Exploration (UEE) with an Unmanned Ground Vehicle (UGV) is extremely challenging. This report investigates a frontier exploration approach, in simulation, that leverages Simultaneous Localization And Mapping (SLAM) to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, three-dimensional (3-D) LIDAR, and Red, Green, Blue and Depth (RGBD) cameras. The main goal of this effort is to leverage frontier-based exploration with a UGV to produce a 3-D map (up to 10 cm resolution). The solution provided leverages the Robot Operating System (ROS).