Robot Motion Sensing for Human-Aware Navigation Around Moving Bodies
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Solution Overview
Problem
Current robots lack the ability to differentiate between people, animals, and objects, leading to inefficient navigation and potential harm, and existing recognition systems are often expensive and ineffective in dynamic environments.
Innovation Solution
A robot equipped with multiple sensor units, including LIDAR, that detect motion and characteristics to differentiate between people, animals, and objects, allowing it to adjust its behavior accordingly, such as slowing down or navigating around them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the robot always slows down when interacting with moving bodies, then safety around people and animals is improved, but navigation efficiency and speed are worsened
Solution Approach 1:
The robot applies different behavior characteristics to different types of moving bodies. It identifies people and animals through sensor data analysis and applies cautious navigation (slowing down) specifically to them, while maintaining normal speed for inanimate objects. This localized differentiation resolves the contradiction by making safety measures selective rather than universal.
Solution Approach 2:
The robot dynamically adjusts its navigation behavior based on real-time identification of moving bodies. When people or animals are detected, the robot transitions to cautious mode with reduced speed; when only inanimate objects are present, it maintains efficient navigation speed. This dynamic adaptation allows the system to optimize both safety and efficiency based on current environmental conditions.
2Productivity
If the robot tries to navigate around moving bodies that are also moving, then path efficiency is improved, but path deviation and complexity are worsened
Solution Approach 1:
The robot applies different navigation strategies based on the type of moving body detected. For people and animals, it uses cautious navigation with potential path adjustments. For inanimate objects, it employs simple avoidance maneuvers. This differentiated approach reduces unnecessary path complexity while maintaining efficiency.
3Measurement precision
If the robot uses advanced recognition algorithms to identify people, then detection accuracy is improved, but computational cost and processing time are worsened
Solution Approach 1:
The robot uses a two-stage detection approach: first applying simpler, faster sensor-based motion detection to identify potential targets, then applying more sophisticated algorithms only when needed to differentiate between people, animals, and objects. This partial application of complex algorithms reduces computational overhead while maintaining sufficient accuracy for navigation decisions.
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
Enables safer and more efficient interactions with moving bodies, improving confidence in autonomous robot operation and reducing injuries by accurately recognizing and responding to people and animals.
Implementation Method 1
A robot equipped with multiple sensor units, including LIDAR, that detect motion and characteristics
Implementation Method 2
Each sensor unit can be configured to generate sensor data indicative of a portion of a moving body at a plurality of times
Data Source
Figure 1
Figure 2
Figure 3A~3B
AI summary
Systems and methods for detection of people are disclosed. In some exemplary implementations, a robot can have a plurality of sensor units. Each sensor unit can be configured to generate sensor data indicative of a portion of a moving body at a plurality of times. Based on at least the sensor data, the robot can determine that the moving body is a person by at least detecting the motion of the moving body and determining that the moving body has characteristics of a person. The robot can then perform an action based at least in part on the determination that the moving body is a person.