Towards Modularity: Integration Strategy of Radar into a LiDAR Based Robotics Mapping Platform

Removing Combat Engineers, first responders, and disaster relief workers from dangerous situations remains a major motivation for researching semi-autonomous mapping platforms. The successful adoption of such systems requires the implementation of a series of complex sensors collecting, processing, and storing terabytes of data, in near real-time. Operations in uncertain and austere environments has great potential for sensor and computational hardware unavailability and damage; robustness to these difficulties requires careful planning and dedicated practices. While simulation allows for rapid creation and testing of such complicated robotic systems and algorithms, development in simulation and on hardware introduces additional complications. This research explores these challenges and proposes a conventional workflow method for modular development of hardware and software in parallel. The Large-group Parallel Simulation-Hardware Development (LaPaSHD) workflow arose from years of US Army Corps of Engineers (USACE) Engineer Research and Development Center’s (ERDC) research with Unmanned Ground Vehicles (UGV). LaPaSHD, system requirements and considerations, best practices, and the challenges motivating this workflow are introduced through a case study: incorporating radar systems into an existing LiDAR based simulated platform.