3D Occlusion Simulation for Autonomous Vehicle Perception
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Solution Overview
Problem
Existing simulation techniques for autonomous vehicles often inaccurately represent object occlusions, requiring expensive resources like multiple GPUs, which may be costly and unavailable, leading to unrealistic or unsafe simulations.
Innovation Solution
The method involves simulating a perception component's output without running it, using a three-dimensional representation of the environment to generate a depth buffer and occlusion grid, which accurately models object occlusions, reducing resource requirements by using a simpler simulator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If more resource-intensive simulation techniques are used to accurately simulate occlusion, then measurement precision of object occlusions is improved, but use of energy and device complexity increase significantly requiring ten or more GPUs
Solution Approach 1:
The patent creates simplified 2D projections (copies) of 3D objects from depth buffers and uses these projections to determine occlusions. Instead of running complex perception algorithms, the system copies depth information and processes it through simplified 2D geometric operations, achieving accurate occlusion detection with minimal computational resources.
Solution Approach 2:
The patent replaces complex mechanical/computational perception systems with a streamlined process using depth buffers and 2D projection mathematics. By substituting the need for full perception component execution with direct depth buffer processing and geometric projection, the system achieves the same occlusion detection function with fraction of the computational cost.
2Measurement precision
If more resource-intensive simulation techniques are used to accurately simulate occlusion, then measurement precision of object occlusions is improved, but device complexity increases requiring ten or more GPUs
Solution Approach 1:
The patent creates simplified 2D projections (copies) of 3D objects from depth buffers and uses these projections to determine occlusions. Instead of running complex perception algorithms, the system copies depth information and processes it through simplified 2D geometric operations, achieving accurate occlusion detection with minimal computational resources.
Solution Approach 2:
The patent replaces complex mechanical/computational perception systems with a streamlined process using depth buffers and 2D projection mathematics. By substituting the need for full perception component execution with direct depth buffer processing and geometric projection, the system achieves the same occlusion detection function with fraction of the computational cost.
3Device complexity
If a simplistic simulator is used, then device complexity and resource requirements are reduced, but measurement precision of object occlusions deteriorates causing inaccurate visibility representation
Solution Approach 1:
The patent works in 2D projection space derived from 3D depth buffers rather than full 3D space. By transforming the problem into 2D image space where occlusions manifest as simple projection overlaps, the system achieves accurate occlusion detection with computationally simple 2D geometric operations instead of complex 3D ray tracing or perception algorithms.
Solution Approach 2:
The patent creates simplified 2D projections (copies) of 3D objects from depth buffers and uses these projections to determine occlusions. Instead of running complex perception algorithms, the system copies depth information and processes it through simplified 2D geometric operations, achieving accurate occlusion detection with minimal computational resources.
4Productivity
If a simplistic simulator is used, then resource requirements are reduced, but reliability of simulation results deteriorates providing inaccurate object visibility data
Solution Approach 1:
The patent works in 2D projection space derived from 3D depth buffers rather than full 3D space. By transforming the problem into 2D image space where occlusions manifest as simple projection overlaps, the system achieves accurate occlusion detection with computationally simple 2D geometric operations instead of complex 3D ray tracing or perception algorithms.
Solution Approach 2:
The patent creates simplified 2D projections (copies) of 3D objects from depth buffers and uses these projections to determine occlusions. Instead of running complex perception algorithms, the system copies depth information and processes it through simplified 2D geometric operations, achieving accurate occlusion detection with minimal computational resources.
Data Source
AI summary
Simulating output of a perception system may comprise receiving scenario data indicating a position associated with a simulated sensor and a position and/or identifier of an object, and instantiating a three-dimensional representation of an environment and the object (i.e., a simulated environment). The system may generate depth data indicating distances and/or positions of surfaces in the simulated environment relative to the simulated sensor position and determine a three-dimensional region of interest based at least in part on the depth data associated with at least a portion of the object. In some examples, the three-dimensional region of interest may be smaller than a size of the object, due to an occlusion by topology of the simulated environment and/or another object in the simulated environment.