Multi-UAV Action Coordination With Dynamic Obstacle Avoidance
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Solution Overview
Problem
Coordinating the movement of multiple unmanned aerial vehicles (UAVs) and detecting obstacles in their surroundings is challenging, particularly in multi-axis spatial orientation, as existing systems struggle to synchronize actions and avoid obstacles effectively.
Innovation Solution
A system and method that utilize sensors and computing devices to track targets, generate composite datasets from multiple perspectives, and alter moving paths of UAVs to maintain relative positions and avoid obstacles, allowing coordinated actions and obstacle detection through image recognition and path adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple UAVs are deployed to track a target and perform coordinated actions, then the system's capability to capture multi-perspective data and perform complex tasks is improved, but the difficulty of coordinating their movements and synchronizing actions increases
Solution Approach 1:
A central controller acts as an intermediary between multiple UAVs, receiving control inputs and distributing coordinated commands to each UAV. The controller generates individual control outputs for each UAV based on the desired coordinated formation and actions, simplifying the coordination complexity by centralizing the computation and communication management.
2Measurement precision
If UAVs are equipped with sensors and imaging equipment to detect obstacles and track targets, then the measurement precision and detection capability are improved, but the weight and energy consumption of the UAVs increase
Solution Approach 1:
Multiple sensing functions (obstacle detection, target tracking, navigation) are merged into integrated sensor systems on each UAV. The sensor data from multiple UAVs is also combined at the central controller to create a comprehensive situational awareness, improving detection precision while optimizing the sensor payload on individual UAVs.
3Stability of the object's composition
If UAVs maintain fixed relative positions to each other for coordinated actions, then the stability of the formation is improved, but the ability to adapt to moving targets and dynamic environments decreases
Solution Approach 1:
The UAV formation transitions from static fixed positions to dynamic relative positioning. Each UAV continuously adjusts its position and orientation based on the target's movement and environmental conditions, while maintaining coordinated formation through real-time control commands from the central controller that preserve formation stability.
4Reliability
If real-time coordination and obstacle avoidance are implemented, then the reliability and safety of UAV operations are improved, but the computational load and communication requirements increase
Solution Approach 1:
The central controller pre-computes coordinated flight paths and obstacle avoidance strategies based on predicted target movement and known environmental obstacles. By planning trajectories in advance and continuously adjusting them based on real-time sensor data, the system reduces the computational load during critical flight phases while maintaining safety and reliability.
Data Source
AI summary
The present disclosure relates to systems, methods, and computer-readable storage devices for the coordination of actions between movable objects. For example, a method may coordinate actions between at least a first and a second movable object. The method may detect, by the first movable object, the position of a target. The method may control the position of a first movable object based on the position of the target. A command may be received for the first movable object to perform an action in coordination with the second movable object. In some embodiments, the command may be to take images of the target to create a bullet time effect.