Coordinated localization seeks to fuse all sources of position information, including signals of opportunity like GPS, and calculate accurate high-level location and at the same time low-level location. This capability has been demonstrated to work in many situations, with the focus on GPS-denied environments.
In many cases, GPS is not available or the accuracy of GPS positioning is too low to enable multiple manned or unmanned systems to successfully achieve mission objectives. Robotic Research’s patented localization framework combines the estimated individual solutions of multiple robots into one cohesive optimal solution. This coordinated localization framework enables a convoy of autonomous vehicles to precisely follow a lead vehicle, and it enables multiple robotic systems to generate a combined map in a GPS-denied area.
The framework functions by allowing each asset in the network to share their best individual estimate of their trajectory, as well as any signals of opportunity, to include GPS, ultra-wideband (UWB) radios, and registration from video and LIDAR. Updates from perception algorithms such as map registration and landmark detection can be used by the optimization algorithm to “close the loop,” providing the best estimate for not just the current pose of each device, but the best estimate for the entire trajectory of all assets. Our framework provides a high-accuracy, real-time localization solution in a variety of GPS and GPS-denied situations, featuring both manned and unmanned ground vehicles, aerial dismounts, and dismounts.