Stair Tracker Perception for Robust Stair Edge Fitting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robots face challenges in navigating stairs due to poor sensor data, particularly during stair ascent and descent, which can lead to inaccurate detection of edges and risers, resulting in potential missteps and collisions.
Innovation Solution
A stair tracker system that processes sensor data to detect and track stair features, generating a staircase model by identifying edges, walls, and heights, and refining these detections over time to improve accuracy and robustness in stair navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot uses sensor data to detect stair edges, then the robot can identify stair features for navigation, but the detection accuracy deteriorates due to poor sensor data quality
Solution Approach 1:
The system performs preliminary actions by detecting edges at multiple time steps before making a final determination. The edge detection process captures candidate edges at different moments, allowing the system to pre-process and compare multiple detection results before selecting the most reliable edge representation, thereby improving accuracy despite poor sensor data quality
Solution Approach 2:
The system implements feedback by comparing detected edges across multiple time steps and using this comparison to refine the final edge detection. The detection results from previous time steps serve as feedback to validate or correct current detections, enhancing both accuracy and reliability through iterative refinement
2Productivity
If the robot traverses stairs quickly, then productivity increases, but the risk of missteps and collisions increases due to inaccurate edge detection
Solution Approach 1:
The system performs preliminary edge detection and validation across multiple time steps before the robot actually traverses the stair. This advance detection and comparison process ensures that accurate edge information is established beforehand, allowing the robot to move quickly while maintaining safety through pre-validated navigation data
Solution Approach 2:
The system provides beforehand cushioning by detecting and validating multiple edge candidates before traversal occurs. This preparatory validation creates a buffer of confidence in the detected edges, allowing the robot to traverse faster while the pre-established accurate edge information acts as a protective measure against missteps
Data Source
AI summary
A method for perception and fitting for a stair tracker includes receiving sensor data for a robot adjacent to a staircase. For each stair of the staircase, the method includes detecting, at a first time step, an edge of a respective stair of the staircase based on the sensor data. The method also includes determining whether the detected edge is a most likely step edge candidate by comparing the detected edge from the first time step to an alternative detected edge at a second time step, the second time step occurring after the first time step. When the detected edge is the most likely step edge candidate, the method includes defining, by the data processing hardware, a height of the respective stair based on sensor data height about the detected edge. The method also includes generating a staircase model including stairs with respective edges at the respective defined heights.