Datacenter UAV Navigation Using Visual Tags After Connection Loss
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Solution Overview
Problem
Monitoring and reporting the operating state of a datacenter in real-time or near-real time is challenging due to the complexity, variability, and dynamic nature of datacenter components and processes.
Innovation Solution
Implementing autonomous aerial imaging and environmental sensing systems using unmanned aerial vehicles (UAVs) that execute a connectivity-enabled navigation process and switch to an autonomous navigation process when connection to the server is lost, utilizing visual tags for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If connectivity-enabled navigation is used for data collection, then real-time monitoring capability is improved, but system reliability deteriorates when connection is lost
Solution Approach 1:
Visual tags serve as intermediary markers positioned throughout the datacenter that enable the UAV to determine its location and navigate autonomously when server connection is lost. The tags act as a mediator between the UAV's navigation system and the physical environment, providing reference points for autonomous operation.
Solution Approach 2:
Visual tags are pre-positioned throughout the datacenter environment before the UAV mission begins. This preliminary placement of navigation markers enables the UAV to execute autonomous navigation without requiring real-time connection to the server, resolving the reliability issue when connections are lost.
2Reliability
If autonomous navigation using visual tags is implemented, then navigation reliability without connection is improved, but device complexity increases
Solution Approach 1:
The UAV equips itself with an onboard imaging system and visual tag recognition capability, enabling it to autonomously detect and navigate to visual tags without external assistance. This self-service approach allows the UAV to maintain autonomous navigation capability while keeping the system relatively simple.
Solution Approach 2:
The patent replaces complex mechanical navigation systems with an optical-based solution using visual tags and an onboard imaging system. This substitution simplifies the navigation system by using vision-based recognition instead of complex mechanical positioning or communication infrastructure.
3Measurement precision
If connectivity-enabled navigation is used, then navigation accuracy is improved, but productivity deteriorates when connection is lost causing mission interruption
Solution Approach 1:
The navigation system dynamically switches between connectivity-enabled mode (when server connection is available) and autonomous mode (when connection is lost). This dynamic adaptation allows the UAV to maintain navigation accuracy through visual tag recognition while ensuring continuous productivity without mission interruption.
Solution Approach 2:
The system changes its operational parameters based on connection status - using server-provided navigation data when connected, and switching to visual tag-based autonomous navigation when disconnected. This parameter change ensures both navigation accuracy and continuous productivity regardless of connection status.
4Adaptability or versatility
If visual tags are positioned throughout the datacenter, then autonomous navigation capability is improved, but device complexity increases due to additional components
Solution Approach 1:
Visual tags use distinct visual characteristics (colors, patterns, or geometric features) that are easily distinguishable by the UAV's onboard imaging system. This approach improves autonomous navigation capability by making tags highly visible and recognizable without requiring complex electronic components or active transmitters.
Solution Approach 2:
Visual tags are simple, inexpensive markers that can be easily deployed throughout the datacenter environment. These passive visual markers provide robust autonomous navigation capability without requiring complex, expensive, or power-consuming components, keeping the overall system simple while enhancing adaptability.
Data Source
AI summary
Methods, systems and apparatus, including computer programs encoded on computer storage medium, for autonomous aerial imaging and environmental sensing of a datacenter. In one aspect a method includes executing, within a datacenter and by an unmanned aerial vehicle (UAV) in data communication with a server, a connectivity-enabled navigation process to collect data from the datacenter; determining, during execution of the connectivity-enabled navigation process and by the UAV, that connection to the server is lost so that the connectivity-enabled navigation process cannot be continued; and in response to determining that connection to the server is lost, executing, by the UAV, an autonomous navigation process until the connection to the server is recovered, wherein the autonomous navigation process navigates the datacenter using visual tags positioned in the datacenter.