Three-Dimensional Velocity Obstacle Method for Uncoordinated Avoidance Maneuvers of Unmanned Aerial Vehicles

Abstract

This paper proposes a novel avoidance method called the Three-Dimensional Velocity Obstacle (3DVO) method. The method is designed for Unmanned Aerial Vehicle (UAV) applications, in particular to autonomously handle uncoordinated multiple encounters in an integrated airspace, by exploiting the limited space in a three-dimensional manner. The method is a three-dimensional extension of the Velocity Obstacle method that can reactively generate an avoidance maneuver by changing the vehicle velocity vector based on the encounter geometry. Adverse maneuvers of the obstacle are anticipated by introducing the concept of a buffer velocity set, which ensures that the ownship will diverge with sufficient space in case of sudden imminence. A three-dimensional resolution is generated by choosing the right plane for avoidance, in which the UAV conducts a pure turning maneuver. Implementation of the 3DVO method is tested in several simulations that demonstrate its capability to resolve various three-dimensional conflicts. A validation using Monte Carlo simulations is also conducted in stressful super-conflict scenarios, which results in zero collisions occurrences for the entire 25,000 samples. Nomenclature BV Buffer Velocity set CC Collision Cone set P φ Avoidance Plane at the angle φ RV i Obstacle Reachable Velocity set S pz Protected Zone VO P φ Velocity Obstacle section on Avoidance Plane-φ VO Velocity Obstacle set α vo Opening angle of the Velocity Obstacle Cone, [-] ∆t Time-step of the VO set generation, [s] δ P Dihedral angle of the avoidance-plane from the XY-plane, [-] ω a.cr Critical avoidance turning rate, [-/s] ω avo Avoidance turning rate, [-/s] φ P Angle of Avoidance Plane around X-axis ψ oi Azimuth angle of the obstacle-i from the ownship, [-] σ col Standard Distribution of Collision Probability, [-] θ oi Elevation angle of the obstacle-i from the ownship, [-] A vo Apex position of the Velocity Obstacle cone, [m] D vo Velocity Obstacle cone symmetric axis vector, [m] E φ vo Escaping point of a VO set, [m/s]

Three-Dimensional Collision Avoidance Control for UAVs using Kinematic-based Collision Threat Situation Modeling Approach

“…This strategy was successfully been implemented in planar space with many moving obstacles by Berg et al [11], resulting a behavior of a crowd system of autonomous robots that are cooperatively avoiding collision. Jenie, et al [12] extended the strategy into the three-dimensional space context and developed a VO-based collision avoidance controller for aerial vehicle flights. Jenie, et al also shows the existence of an unlimited number of ways to avoid collision (re-illustrated in Figure 1), from which a working CA controller has to search to obtain an optimal solution.…”

Initial Study of An Effective Fast-time Simulation Platform for Unmanned Aircraft System Traffic Management

“…al. 12 proposed a method for uncoordinated avoidance maneuvers of UASs and conducted Monte Carlo simulation to verify the proposed method. The second type of simulation deals with encounter models and is usually designated as Conflict Detection and Resolution (CD&R) research.…”

“…These unique characteristics demand both sUASs' dynamic sytem models and controller models for an effective UTM fast-time simulation platform, such that evaluations on this platform can provide sufficient accuracy, especially for dense operations. Although recent research 11,12,15,16 started to expand vehicles' speed ranges in an attempt to represent small UASs or multi-rotor vehicles, negligence of modeling sUAS controllers will yield inaccurate trajectory predictions, especially at low altitude airspace where wind changes very often, eventually lead to invalid simulations. Therefore, besides the vehicle dynamic sysmte, vehicle's control system needs to be modeled as well.…”

Experimental maneuverability and agility quantification for rotary unmanned aerial vehicle

“…As an alternative, one can estimate a representative bandwidth based on the 10-90% rise time of the UAV's measured attitude change. The formula assumes a second-order behavior and a damping ratio of 0.7 in equation (3). 16 This metric is not in ADS-33E, so no reference value is available.…”

“…1 Rotary (or rotorcraft) UAVs are of interest for various missions such as short-range parcel/medicine transportation, close-range infrastructure inspection or, just for fun, drone racing. 2 Most UAV control research is focused on optimal control, obstacle detection, and autonomous navigation, 3,4 yet very little is focused on quantifying the inherent high maneuverability and agility of small UAVs, more specifically multicopters (or multirotors). As multicopters evolve both to extremely large and small sizes, retaining high agility is important.…”