τ-θ Space Mapping for Mobile Body Collision Avoidance
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Solution Overview
Problem
Conventional collision avoidance systems for vehicles require significant computational resources for XY space conversion, which hampers their performance in real-time path planning under various environments.
Innovation Solution
The system employs a τ-θ space mapping approach, using a collision prediction time (τ) and target portion angle (θ) to reduce computational demands, allowing for efficient path planning and collision avoidance with minimal processing requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If XY space conversion processing is used to project sensor input into metric space for path planning, then collision avoidance accuracy is improved, but computational load increases enormously affecting system performance
Solution Approach 1:
The patent changes the coordinate system parameters from conventional XY metric space to a new τ-θ space where τ represents collision prediction time and θ represents target portion angle. This parameter transformation fundamentally alters the mathematical representation of spatial information, enabling collision risk assessment through temporal and angular relationships rather than traditional Cartesian coordinates. The transformation formulas convert sensor data (range R, azimuth angle φ, elevation angle ψ) into τ-θ coordinates through specific mathematical relationships, achieving accurate collision prediction with reduced computational complexity.
2Adaptability or versatility
If real-time path planning is executed under various environments, then collision avoidance capability is improved, but hardware processing capability requirements increase
Solution Approach 1:
The patent transforms the coordinate system parameters from conventional XY metric space to a new τ-θ space where τ represents collision prediction time and θ represents target portion angle. This parameter transformation fundamentally alters the mathematical representation of spatial information, enabling collision risk assessment through temporal and angular relationships rather than traditional Cartesian coordinates. The transformation formulas convert sensor data (range R, azimuth angle φ, elevation angle ψ) into τ-θ coordinates through specific mathematical relationships, achieving accurate collision prediction with reduced computational complexity.
Data Source
AI summary
A mobile body spatial information calculation apparatus according to an embodiment includes an input section configured to receive sensor information including information on one or more target objects based on a position of an own mobile body from a sensor apparatus, an object recognition section configured to recognize the target object based on the sensor information, a calculation section configured to calculate a collision prediction time and a target portion angle based on the sensor information on the target object recognized by the object recognition section, and a spatial information generation section configured to generate spatial information according to the collision prediction time and the target portion angle using the collision prediction time and the target portion angle calculated by the calculation section and store the generated spatial information.