“The main goal of our paper was to leverage arbitrary 3-D trajectories for a robot (UAV or UGV) equipped with an on-board trajectory estimation sensor,” Ninad Jadhav, one of the researchers who carried out the study, told TechXplore. “This allows a Wi-Fi-signal-receiving robot to estimate the spatial direction (in azimuth and elevation) of other neighboring robots by capturing all the wireless signal paths traveling between the transmitting and receiving robot (which we call AOA profile). Additionally, we also characterized how the trajectory shape impacts the AOA profile using Cramer Rao bound.”
In their previous studies, Jadhav and his colleagues focused on robot collaboration scenarios in which the robots followed 2-D trajectories with a limited set of geometries (e.g., linear or curved). The new system they created, on the other hand, is applicable to scenarios where robots are moving freely, following a wider range of trajectories. “Another constraint that we relaxed in the paper was the requirement for a Wi-Fi signal-transmitting robot to remain stationary while the receiving robot moves and generates an AOA profile,” Jadhav said. “The new approach we devised accounts for continuous mobility of all robots irrespective of whether its transmitting or receiving Wi-Fi packets.”
As Jadhav and his colleagues wanted to devise a system that only used sensors mounted directly on robots, they also examined the impact of local trajectory estimations, which are intrinsically imperfect and prone to errors, on the patterns in which Wi-Fi signals travel between two robots (AOA profiles). The researchers then evaluated the system they developed in a series of experiments using real robots, achieving highly promising results.
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