Mobile Manipulation Platform for Autonomous Indoor Inspections in Low-Clearance Areas

Mobile manipulators have been used for inspection, maintenance and repair tasks over the years, but there are some key limitations. Stability concerns typically require mobile platforms to be large in order to handle far-reaching manipulators, or for the manipulators to have drastically reduced workspaces to fit onto smaller mobile platforms. Therefore we propose a combination of two widely-used robots, the Clearpath Jackal unmanned ground vehicle and the Kinova Gen3 six degree-of-freedom manipulator. The Jackal has a small footprint and works well in low-clearance indoor environments. Extensive testing of localization, navigation and mapping using LiDAR sensors makes the Jackal a well developed mobile platform suitable for mobile manipulation. The Gen3 has a long reach with reasonable power consumption for manipulation tasks. A wrist camera for RGB-D sensing and a customizable end effector interface makes the Gen3 suitable for a myriad of manipulation tasks. Typically these features would result in an unstable platform, however with a few minor hardware and software modifications, we have produced a stable, high-performance mobile manipulation platform with significant mobility, reach, sensing, and maneuverability for indoor inspection tasks, without degradation of the component robots' individual capabilities. These assertions were investigated with hardware via semi-autonomous navigation to waypoints in a busy indoor environment, and high-precision self-alignment alongside planar structures for intervention tasks.

A Robust and Rapidly Deployable Waypoint Navigation Architecture for Long-Duration Operations in GPS-Denied Environments

For long-duration operations in GPS-denied environments, accurate and repeatable waypoint navigation is an essential capability. While simultaneous localization and mapping (SLAM) works well for single-session operations, repeated, multi-session operations require robots to navigate to the same spot(s) accurately and precisely each and every time. Localization and navigation errors can build up from one session to the next if they are not accounted for. Localization using a global reference map works well, but there are no publicly available packages for quickly building maps and navigating with them. We propose a new architecture using a combination of two publicly available packages with a newly released package to create a fully functional multi-session navigation system for ground vehicles. The system takes just a few hours from the beginning of the first manual scan to perform autonomous waypoint navigation.