R‐ADVANCE: Rapid Adaptive Prediction for Vision‐based Autonomous Navigation, Control, and Evasion

• Published in: Journal of field robotics Vol. 35; no. 1; pp. 91 - 100
• Main Authors: Escobar‐Alvarez, Hector D., Johnson, Neil, Hebble, Tom, Klingebiel, Karl, Quintero, Steven A. P., Regenstein, Jacob, Browning, N. Andrew
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.01.2018
• Subjects: Adaptive control; aerial robotics; Algorithms; Autonomous navigation; BASIC (programming language); Control algorithms; Global positioning systems; GPS; GPS‐denied; High‐speed; Microprocessors; Navigation; Obstacle avoidance; Odometers; Parallel processing; perception; Satellite navigation systems; Unmanned aerial vehicles; Video data; Visual perception driven algorithms
• ISSN: 1556-4959; 1556-4967
• DOI: 10.1002/rob.21744

In this article, we present a monocular visual reactive navigation system capable of navigating at high speeds, without GPS, in unknown complex cluttered environments. The system, called R‐ADVANCE (Rapid Adaptive Prediction for Vision‐based Autonomous Navigation, Control, and Evasion), consists of a set of biologically inspired visual perception and reactive control algorithms that provide low‐computation reactive obstacle avoidance while navigating at high speeds in search of a goal object. These algorithms, along with basic planning, and augmented with low‐precision visual odometry, were implemented on a micro unmanned aerial vehicle and tested in a number of challenging environments. While each of the individual algorithmic and hardware elements has been previously studied in limited environments, this work is the first time that these novel components have been integrated and flight‐tested. To achieve fast flight, an NVIDIA Tegra TK1 was used as the main processor, allowing us to parallelize the system to process 1280 × 720 video streams at 40 fps, reaching flight speeds up to 19 m/s (≈68 km/h) or 42 mph.