Increasing autonomy of UAVs

Abstract

U nmanned aerial vehicles (UAVs) are acquiring an increased level of autonomy as more complex mission scenarios are envisioned [1]. For example, UAVs are being used for intelligence, surveillance, and reconnaissance missions as well as to assist humans in the detection and localization of wildfires [2], tracking of moving vehicles along roads [3], [4], and performing border patrol missions [5]. A critical component for networks of autonomous vehicles is the ability to detect and localize targets of interest in a dynamic and unknown environment. The success of these missions hinges on the ability of the algorithms to appropriately handle the uncertainty in the information of the dynamic environment and the ability to cope with the potentially large amounts of communicated data that will need to be broadcast to synchronize information across networks of vehicles. Because of their relative simplicity, centralized mission management algorithms have previously been developed to create a conflict-free task assignment (TA) across all vehicles. However, these algorithms are often slow to react to changes in the fleet and environment and require high bandwidth communication to ensure a consistent situational awareness (SA) from distributed sensors and also to transmit detailed plans back to those sensors. More recently, decentralized decision-making algorithms have been proposed [6]-[8] that reduce the amount of communication required between agents and improve the robustness and reactive ability of the overall system to bandwidth limitations and fleet, mission, and environmental variations. These methods focus on individual agents generating and maintaining their own SA and TA, relying on periodic intervehicle

System Safety Modeling of Alternative Geofencing Configurations for small UAS

“…There is growing research in the use of autonomy for UAS, especially as missions become more complex (NRC, 2014;How et al, 2009). However, there are a number of issues confronting autonomous operations for UAS that deal with safety and latency (McKinlay, 2014;Wagner, 2008).…”

Visual sensing for developing autonomous behavior in snake robots

“…This behavior is generally done where the operator has a clear view of both the snake and pole. The development of the 3D capable sensor head has allowed for the automation of the pole climbing behavior 1 . In this section we outline the basic principles behind this automation.…”

“…The cylinder segmentation algorithm is calibrated for poles with a diameter in the range of 5 cm to 20 cm, which corresponds to the size of poles that can be climbed by the snake robot. 1 A video showing autonomous pole climbing has been submitted with this paper. This video is also available via http://youtu.be/X3p10HWVHsc (This is an unlisted video and can only be seen using this link) 2 2) Locomotion: Once the pole is localized, the snake proceeds to move towards it.…”

“…A successful field robot must be able to sense, plan, and act; three essential components of an autonomous system [1], [2]. Research in snake robots has focused on the acting component; with various work being done to improve the control and fundamental understanding of snake locomotion [3], [4], [5], [6].…”

Assessing operator strategies for real-time replanning of multiple unmanned vehicles

“…This simulation environment functions as a computer simulation but also supports actual flight and ground capabilities [19]; all the decision support displays described here have operated actual small air and ground UxVs in real-time.…”