Autonomous Vehicle Maneuver Recognition for On-Demand Payload Triggering
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Solution Overview
Problem
Autonomous vehicles often require expensive auxiliary communication systems to control payloads, which can affect navigation performance and consume power and data storage resources unnecessarily, especially when operating in always-on states outside of intended targets.
Innovation Solution
Implementing a vehicle navigation sensor system that monitors movements to match predefined gesture patterns, allowing payload events to be triggered only when specific maneuvers are identified, thereby enabling controlled operation of payloads without continuous communication systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If an auxiliary communication system is used to control payloads, then payload control capability is improved, but system cost and complexity increase
Solution Approach 1:
The patent combines the navigation sensor system and payload control system into a unified architecture. The navigation sensor processor detects vehicle maneuvers and directly triggers payload operations, merging the communication function into the existing navigation system and eliminating the need for separate auxiliary communication hardware.
Solution Approach 2:
The system uses the vehicle's own navigation sensor data to control payloads, making the vehicle self-sufficient. The navigation processor autonomously interprets maneuver patterns and generates payload control commands without external communication systems, allowing the vehicle to control its own payloads using internally generated information.
2Ease of operation
If payload operates in always-on state, then payload responsiveness is improved, but power consumption and data storage increase
Solution Approach 1:
Instead of continuous operation, the payload operates periodically based on detected maneuver patterns. The system monitors navigation data continuously but triggers payload activation only when specific maneuver patterns are identified, creating a periodic on-demand operation mode that reduces overall power consumption while maintaining responsiveness when needed.
Solution Approach 2:
The system performs preliminary detection of maneuver patterns using navigation sensors before activating the payload. By continuously monitoring vehicle movements and identifying predefined gesture patterns in advance, the system prepares for payload activation, ensuring rapid response when the actual capture or action moment occurs without keeping the payload continuously active.
3Reliability
If payload operates in always-on state, then payload capture capability is improved, but data storage resources are consumed unnecessarily
Solution Approach 1:
The payload operates periodically based on detected maneuver patterns rather than continuously. Data capture is triggered only during identified maneuver events, creating a periodic capture pattern that ensures reliable capture of intended targets while avoiding unnecessary data storage consumption during non-event periods.
Solution Approach 2:
The navigation sensor system autonomously identifies when payload activation is needed based on maneuver pattern recognition. This self-service approach ensures the payload captures data only when the vehicle performs meaningful maneuvers, automatically filtering out unnecessary capture events and optimizing data storage resource utilization without external intervention.
Data Source
AI summary
Autonomous vehicles may include one or more onboard devices to perform various actions, such as a still image capture device. In contrast with using an auxiliary communication system to control a payload, a vehicle navigation sensor is used to monitor autonomous vehicle movements to match a predefined vehicle maneuver event, and trigger a payload event based on identification of the vehicle maneuver event. For example, this allows an autopilot system or a remote drone pilot to initiate an image capture device or send other commands based on vehicle maneuver event recognition.