Robot Blind Spot Risk Estimation for Collision-Aware Navigation
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Solution Overview
Problem
Robots operating in complex spaces like airports and offices face challenges in detecting and avoiding unexpected obstacles, particularly those in blind spots where sensors may not cover, leading to potential collisions.
Innovation Solution
A method that utilizes a two-dimensional or three-dimensional map with height information, combining data from LiDAR sensors and depth cameras to identify blind spots and adjust the robot's speed and direction to avoid collisions, by fusing sensing data with map information to enhance detection accuracy and prevent collisions with unexpected obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot uses sensors to detect obstacles in its traveling path, then it can avoid known obstacles, but it cannot detect unexpected obstacles in blind spots
Solution Approach 1:
The robot performs preliminary actions by slowing down before reaching blind spots (areas not covered by sensors) and preliminarily determines whether obstacles exist in these blind spots before fully entering them. This proactive approach allows the robot to prepare for potential obstacles before they become a collision risk, improving detection reliability in areas that would otherwise be undetectable.
2Productivity
If the robot travels at normal speed based on map information, then productivity is maintained, but collision risk with unexpected obstacles increases
Solution Approach 1:
The robot dynamically adjusts its traveling speed based on real-time conditions. When approaching blind spots or areas with potential obstacles, the robot automatically slows down. When the path is clear and safe, it resumes normal speed. This dynamic speed adjustment maintains productivity overall while significantly improving collision avoidance reliability in critical zones.
3Reliability
If the robot slows down before blind spots to check for obstacles, then collision risk is reduced, but traveling time increases
Solution Approach 1:
The robot applies partial slowing down only in specific critical zones (blind spots) rather than maintaining reduced speed throughout the entire journey. This selective approach focuses safety measures where they are most needed while minimizing overall time loss. The robot performs just enough slowing down to safely check blind spots, avoiding excessive time consumption in areas where full speed is safe.
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
The solution effectively allows robots to navigate through spaces with reduced collision risks by accurately identifying blind spots and adjusting their path or speed in response to unexpected obstacles, improving their ability to operate safely in complex environments.
Implementation Method 1
combining data from LiDAR sensors and depth cameras
Implementation Method 2
combining data from LiDAR sensors and depth cameras
Data Source
AI summary
The present disclosure relates to a method of identifying an unexpected obstacle and a robot implementing the method. The method includes: by a sensing module of a robot, sensing a blind spot located in a traveling path of the robot; by a control unit of the robot, calculating a probability that a moving object appears in the sensed blind spot; and, by the control unit, controlling the speed or direction of a moving unit of the robot based on the calculated probability.