Autonomous Navigation System Detecting Non-Solid Obstacles
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Solution Overview
Problem
Autonomous navigation systems struggle to effectively detect and avoid non-solid objects, such as fluid substances, in their environment, as existing sensors and navigation methods are primarily designed for solid objects, leading to potential interference or obstacles that can impact vehicle operation and safety.
Innovation Solution
An autonomous navigation system that utilizes sensors to detect non-solid objects by determining their depth relative to the terrain and adjusts the vehicle's route to avoid intersecting with these objects, employing a method that processes sensor data to identify and characterize non-solid objects based on their elevation difference and material composition, and navigates the vehicle along a new route if the depth exceeds a threshold, treating the non-solid object as if it were a solid obstacle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing sensors and navigation methods designed for solid objects are used, then the system can effectively detect and avoid solid obstacles, but the system fails to detect and avoid non-solid objects such as fluid substances
Solution Approach 1:
The sensor system is enhanced to perform multiple detection functions - both solid object detection (via reflection-based sensors like LIDAR and radar) and non-solid object detection (via depth-based sensors and terrain analysis). This multi-functional approach allows the single navigation system to handle diverse object types without requiring separate dedicated systems.
Solution Approach 2:
The system changes detection parameters based on object type - using reflection intensity and surface characteristics for solid objects, while using depth measurement, elevation difference, and material composition analysis for non-solid objects. This parameter adaptation enables reliable detection across different object states.
2Reliability
If the system treats non-solid objects as solid obstacles, then the vehicle can avoid them safely, but the navigation route may become overly conservative and less efficient
Solution Approach 1:
The system applies different avoidance strategies to different spatial regions based on local object characteristics. For non-solid objects, the system calculates specific depth values and compares them against threshold values at each location, allowing the vehicle to navigate through safe regions while avoiding hazardous deep fluid areas, rather than treating all non-solid objects uniformly.
Solution Approach 2:
The navigation route is dynamically adjusted based on real-time depth measurements and object characterization. The system continuously evaluates whether to avoid or navigate through non-solid objects based on current depth readings, allowing flexible route optimization that balances safety and efficiency rather than following fixed conservative paths.
3Measurement precision
If the system uses multiple sensor types to detect non-solid objects, then detection accuracy improves, but the device complexity increases
Solution Approach 1:
The system merges data from multiple sensor types (depth sensors, terrain mapping sensors, material composition sensors) into a unified non-solid object detection framework. By combining these sensor inputs and processing them through integrated algorithms, the system achieves high measurement precision for depth and material identification while avoiding the complexity of managing completely separate detection systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the autonomous navigation system to safely and efficiently avoid non-solid objects, ensuring vehicle operation and occupant safety by accurately detecting and responding to fluid substances and other non-solid materials, even if they pose a risk to navigation.
Implementation Method 1
an ANS which detects and characterizes objects in the environment based on reflection of radar waves, ultrasonic waves, light beams, etc. from solid surfaces of the objects in the environment
Data Source
AI summary
An autonomous navigation system may navigate through an environment in which one or more non-solid objects, including gaseous and/or liquid objects, are located. Non-solid objects may be determined, using sensor data, to present an obstacle or interference based on determined chemical composition, size, position, velocity, concentration, etc. of the objects.