2019/09/17 by Ty Nguyen, Kartik Mohta, Nguyen, Ty +5 · 1 citation
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Target Tracking and Data Fusion in Sensor Networks
paper · pdf · doi:10.48550/arxiv.1909.08200
openalex publication_date 2019/09/17 · openalex created_date 2022/07/24 · openalex updated_date 2026/07/28
We address the localization of robots in a multi-MAV system where external\ninfrastructure like GPS or motion capture systems may not be available. Our\napproach lends itself to implementation on platforms with several constraints\non size, weight, and power (SWaP). Particularly, our framework fuses the\nonboard VIO with the anonymous, visual-based robot-to-robot detection to\nestimate all robot poses in one common frame, addressing three main challenges:\n1) the initial configuration of the robot team is unknown, 2) the data\nassociation between each vision-based detection and robot targets is unknown,\nand 3) the vision-based detection yields false negatives, false positives,\ninaccurate, and provides noisy bearing, distance measurements of other robots.\nOur approach extends the Coupled Probabilistic Data Association Filter\n(CPDAF)[1] to cope with nonlinear measurements. We demonstrate the superior\nperformance of our approach over a simple VIO-based method in a simulation with\nthe measurement models statistically modeled using the real experimental data.\nWe also show how onboard sensing, estimation, and control can be used for\nformation flight.\n