Human-Following Robot Control for Obstacle-Dodging Navigation
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Solution Overview
Problem
Service robots face challenges in interacting with humans in crowded and dynamic environments, requiring the ability to follow a target human while avoiding obstacles without interrupting their mission.
Innovation Solution
A robot system equipped with a detecting device, controlling device, and mobile device that calculates a resultant force parameter to navigate around obstacles while maintaining a stable following of the target human, using a combination of image detection, deep learning neural networks, and vector calculations to adjust its movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot prioritizes following the target human, then the following stability is improved, but the ability to avoid obstacles deteriorates
Solution Approach 1:
The robot dynamically adjusts its motion parameters based on real-time detection of target humans and obstacles. The controlling device calculates motion parameters by integrating following force (attracted to target human) and repulsive force (pushed away from obstacles), allowing the robot to adapt its trajectory dynamically to maintain following stability while avoiding collisions in crowded environments.
2Object-affected harmful factors
If the robot focuses on avoiding obstacles, then the safety is improved, but the following accuracy deteriorates
Solution Approach 1:
The controlling device changes motion parameters by calculating a composite force vector that combines following force (maintaining following accuracy) and repulsive force (ensuring obstacle avoidance). This parameter transformation allows the robot to simultaneously achieve both following precision and collision avoidance by adjusting the resultant motion direction and speed based on real-time force calculations.
3Reliability
If the robot uses complex detection and control algorithms, then the following and obstacle avoidance performance is improved, but the device complexity increases
Solution Approach 1:
The patent introduces a force-based intermediary model where the detecting device and controlling device communicate through force parameters (following force and repulsive force). This intermediary representation simplifies the control logic by transforming complex detection data into intuitive force vectors that can be directly integrated to generate motion commands, reducing overall system complexity while maintaining high performance.
Data Source
AI summary
A system of a robot for human following includes the robot faced toward a first direction. The robot includes a detecting device, a controlling device and a mobile device. The detecting device detects a target human and a obstacle. The controlling device generates a first parameter according to a first vector between the target human and the robot, generates a second parameter according to a second vector between the obstacle and the robot, and generates a driving command according to a first resultant force parameter generated from the first parameter and the second parameter and an angle value between the first direction and the first vector to drive the robot. The mobile device performs the driving command to enable the robot dodging the at least one obstacle and following the target human, simultaneously. A controlling method of a robot for human following is also disclosed herein.