For example, user computing device accesses the horizontal route generated by example process of FIG. Thus, user computing device continues repeating blocks, and to recursively grow the avoidance shape and determine one or more paths around the avoidance shape until a path does not intersect an obstacle.
As will be described in further detail herein, user computing device generates a route and instructs UAV to begin its flight via UAV service The route information can be initiated from a user selecting a destination for the UAV on a mobile device.
Continuing with the example, assume that the violation at intermediary waypoint E was the maximum violation. User computing device may generate avoidance shape using process of FIG. UAV may include one or more lighting devices Example obstacle classifications include a critical avoidance zone and a general avoidance zone.
For example, the same UAV may permit payload container to be placed above power source and vice versa.
User computing device may generate avoidance shape and the third and fourth paths and using process of FIG. Example UAV computing system includes application processorpower sourcecarrier boardautopilot devicepositioning receiverand speed controllers Thus, analysis of tracking data within tracking data store may be used for preventative maintenance by identifying outliers within the tracking data.
In some embodiments, user computing device determines the vertical route following a horizontal route determination, which may prioritize horizontal route planning over vertical route planning. In one example, the UAV may further report operating parameters e.
At blockuser computing device determines one or more paths around the avoidance shape. Example application processor further receives data from one or more imagers Example application processor transmits data to UAV service in near time. In some embodiments, a user initiates the flight of the UAV using user computing device In yet other embodiments, sensor data is transmitted to user computer device for presentation of the sensor data or visualization of the sensor data in a user interface.
In some embodiments, application processor reports status data to UAV service based on a predefined configurable interval such as every second or four times per second. For example, user computing device converts the start location into a sector identifier and requests geospatial data from geospatial cache for the sector identifier, as described herein.
In some embodiments, power source includes a battery manager. For example, an unmanned aerial vehicle may include application processor, one or more propulsion sensors, a communication device wirelessly connected to a cellular network, and additional components.
The start and end location data includes coordinates on a reference system.
Example user interface representation of a horizontal route determination process are illustrated in FIG. The terminology used in the description of the various described embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
Thus, user computing device proceeds to block if the past intersects one or more obstacles. But Landry says this preparation time can be reduced with a few modifications. Geospatial data store may include large amounts of data such as hundreds of gigabytes of data or terabytes of data.
The terminology used in the description of the various described embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
View gallery - 3 images Drone technology sure is promising plenty, but before the public can really warm to the idea of unmanned vehicles zipping around in all directions they want to feel pretty confident that they won't crash into things. At blockuser computing device determines a horizontal route from the start location to the end location.
General avoidance zones may include geospatial data associated with schools, buildings, or any predefined areas that are to be generally avoided in routes but are permissible as start and end locations.
For example, a human pilots an aircraft while the human is located on the ground by reviewing aircraft telemetry and an onboard camera from the aircraft. Small civilian UAVs have no life-critical systemsand can thus be built out of lighter but less sturdy materials and shapes, and can use less robustly tested electronic control systems.
The researchers approached this by loading the plane with a set of 40 to 50 trajectories that it could fly along, which they describe as funnels.
Local minimum and maximum altitudes may change at each waypoint of the route because the respective ground level of each waypoint may change. Abstract: The technology based on ant colony optimization and Voronoi diagram was used to achieve the intelligent route planning for unmanned aircraft.
First, the Voronoi weighted direction diagram was created by the threat sources distribution and the threat costs. UAV Planner is an advanced planning and scheduling application that provides automated route planning and sensor tasking for unmanned aerial vehicles. UAV Planner allows operators, designers and engineers to model their UAV systems and perform operational scheduling and analysis using COTS software.
Ant colony algorithm can bring about route planning for unmanned combat aircraft and obtainthe so lution of the optimal route. Many scholars at home and abroad have studied the route planning method based on ant colony algorithm.
Route Planning of UAV. Abstract—In this paper, we proposed an energy-based ﬂight planning system for Unmanned Aircraft Systems (UAS) Trafﬁc Management (UTM).
Fuel consumption estimation at the ﬂight planning stage is safety critical in general aviation, because energy-related failures are often life. The method of path planning based unmanned, the present invention can be implemented to help in the case of unmanned, by trimming at the time of driving by the vehicle speed, traffic lights to avoid long waiting time, to optimize the driving experience, green carbon travel purposes.
Unmanned aerial vehicle (UAV) was introduced to take road segment traffic surveillance. Considering the limited UAV maximum flight distance, UAV route planning problem was studied.
First, a multi-objective optimization model of planning UAV route for road segment surveillance was proposed, which.Route planning for unmanned aircraft based