Autonomous Perception System Multi-Modality Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current lidar devices for autonomous systems face issues such as low accuracy, high cost, and high interference from external sources, limiting their effectiveness in applications like autonomous vehicles and other sensing systems.
Innovation Solution
A comprehensive perception system incorporating a constellation of probes with multiple sensing modalities like lidar, radar, cameras, and GPS, integrated at both hardware and software levels, which enables concurrent sensing, intelligent resource allocation, and flexible operation to enhance detection confidence and measurement precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current lidar devices are used for autonomous systems, then environmental sensing capability is provided, but measurement precision and accuracy deteriorate
Solution Approach 1:
The patent combines multiple sensing modalities (lidar, radar, cameras, GPS) into a unified perception system that processes data concurrently. This integration allows the system to leverage the strengths of each modality while compensating for individual weaknesses, thereby improving both measurement precision and detection reliability through multi-source data fusion and cross-validation.
Solution Approach 2:
The perception system is designed to perform multiple sensing functions simultaneously using different modalities. Each probe can detect various environmental parameters (distance, velocity, visual information, position) using appropriate sensing technologies, making the system universally applicable to diverse autonomous navigation scenarios while maintaining high precision across different measurement types.
2Reliability
If current lidar devices are used for autonomous systems, then environmental sensing is achieved, but cost increases
Solution Approach 1:
The system divides the sensing function into multiple independent probes, each optimized for specific sensing modalities. This segmentation allows for modular deployment where systems can be configured with appropriate sensor combinations based on application requirements and budget constraints, reducing overall system cost while maintaining reliability through distributed sensing capabilities.
Solution Approach 2:
The perception system incorporates multiple relatively low-cost sensor probes rather than relying on a single expensive high-precision lidar device. By using multiple simpler, more affordable sensors that work together in concert, the system achieves comparable or superior reliability at reduced cost, making autonomous systems more economically viable.
3Measurement precision
If current lidar devices are used for autonomous systems, then basic sensing is provided, but interference from external sources increases
Solution Approach 1:
The system uses multiple sensing modalities as intermediaries to cross-validate environmental information. When one modality experiences interference (e.g., lidar affected by fog or rain), other modalities (radar, cameras) serve as intermediaries to provide alternative measurement paths, maintaining sensing accuracy by selecting or weighting data from the least interfered channels.
Solution Approach 2:
The perception system creates a composite sensing approach by integrating data from diverse modalities (optical, electromagnetic, positional). This composite methodology is analogous to using composite materials - each modality contributes unique properties that, when combined, create a more robust and interference-resistant sensing system than any single modality could provide alone.
Data Source
AI summary
A lidar sensor comprising a laser, an optical sensor, and a processor. The lidar sensor can determine a distance to one or more objects. The lidar sensor can optionally embed a code in beams transmitted into the environment such that those beams can be individually identified when their corresponding reflection is received.