Micro aerial vehicles (MAVs) are agile and have unstable flight dynamics. They require a failsafe method to be navigated through areas even without GPS coverage. The approach of this work is to use only the feature matches between two consecutive images, i.e. optical flow (OF) and inertial cues. The vehicle’s pose and additional intrinsic as well as extrinsic states are estimated continuously to navigate and control the MAV through the area. Optical flow cues and inertial measurement readings are fused in an EKF (extended Kalman filter) framework to estimate a metric 3D body velocity, terrain plane-parameters, terrain plane relative 3D attitude including heading, and metric distance between the camera on the MAV and this plane. The estimates of the EKF provide the vehicle controller with accurate information about the vehicle and the environment in order to navigate the micro-helicopter autonomously through large areas. The system is fully self-contained and all computation is done onboard the MAV in real-time. This eliminates the need of a data link to a ground station and allows standalone operation.
The novelty of the technology is that the full information provided by OF and inertial readings is used to achieve a complete vehicle state estimation. Earlier work of the author on IOF (inertial-optical flow) state estimation for MAVs included estimates of the attitude with respect to a gravity-aligned navigation frame and a metric velocity including inertial biases, visual scale, and transformation between the camera and IMU (inertial measurement unit), turning the platform into a so-called self-calibrating power-on-and-go system. This extended approach additionally allows estimation of the inclination of the terrain towards gravity, the MAV’s heading with respect to this plane, and its metric distance to this plane. The heading and terrain-plane distance are two additional degrees of freedom which are crucial to keep the MAV on a specific course and away from the ground for terrain following. The approach is inherently failsafe since all these states are estimated by only using a minimum of three feature matches in two consecutive camera frames. Neither feature history nor (local) map — which could get corrupted over time — is required. In fact, tests show that the approach is robust enough such that the MAV can be deployed by simply throwing it into the air stabilizing itself quickly. This extends the platform from a power-on-and-go system to a true throw-and-go MAV.
For reconnaissance, exploration, and search and rescue, small-scale helicopters may be the most viable solution because of their hovering and navigational advantages. Small-scale helicopters can even be deployed in cluttered and narrow environments indoors and outdoors with a minimal risk to people or the environment. The light weight of MAVs makes them ideal to carry to and deploy in various different scenarios.
This work was done by Stephan M. Weiss of Caltech for NASA’s Jet Propulsion Laboratory. The software used in this innovation is available for commercial licensing. Please contact Dan Broderick at
This Brief includes a Technical Support Package (TSP).
Autonomous Micro Aerial Vehicle Flight Using Optical Flow and Inertial Cues
(reference NPO49036) is currently available for download from the TSP library.
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Overview
The document is a Technical Support Package from NASA's Jet Propulsion Laboratory (JPL) that focuses on advancements in autonomous micro aerial vehicles (MAVs). It highlights the integration of optical flow and inertial cues for flight control, emphasizing the potential applications of these technologies in various fields.
Key areas of focus include miniaturization of avionic packages, which is crucial for enhancing the capabilities of MAVs. The document discusses the importance of developing robust and fail-safe systems to ensure reliable operations in diverse environments. High-speed flight capabilities are also a significant aspect, allowing MAVs to perform tasks efficiently and effectively.
One of the notable projects mentioned is the AscTec Hummingbird, which operates in hover mode at 1.5 meters above the ground using vision-based navigation. This system demonstrates a high level of precision, with a root mean square (RMS) error in position of approximately 2.9 cm in the x-direction, 3.0 cm in the y-direction, and 0.8 cm in the z-direction. Such accuracy is essential for applications that require close-range operations, such as surveillance and autonomous landing.
The document outlines the high-level autonomy features being developed, including fully autonomous landing-site detection, which enables MAVs to identify and navigate to suitable landing areas without human intervention. This capability is crucial for safe operations, particularly in urban environments where landing sites may be limited or complex. Additionally, the document mentions the potential for autonomous recharging, which would allow MAVs to operate for extended periods without manual intervention.
The research and technology discussed in the document are part of NASA's broader efforts to advance aerospace technologies with commercial and scientific applications. The information is intended to support the dissemination of knowledge and foster collaboration in the field of autonomous aerial systems.
For further inquiries or detailed information, the document provides contact details for the Innovative Technology Assets Management office at JPL, encouraging engagement with those interested in the technological advancements presented.
Overall, this Technical Support Package serves as a comprehensive overview of the current state and future directions of autonomous micro aerial vehicle technology, showcasing the innovative work being done at NASA JPL.
