Autonomous Mobile Robot Route Control for Human-Aware Avoidance
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Solution Overview
Problem
Autonomous mobile robots operating in facilities with people face inefficiencies due to constant environmental changes, leading to potential interference with human movements and decreased operational efficiency when relying solely on predetermined paths.
Innovation Solution
An autonomous mobile robot control system that includes environmental cameras for detecting and tracking moving bodies, estimating their paths, generating avoidance procedures to prevent collisions, and instructing robots to adjust their routes dynamically, thereby enhancing operational efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous mobile robots operate on predetermined paths, then operational simplicity is maintained, but operational efficiency deteriorates due to inability to adapt to environmental changes and human movements
Solution Approach 1:
The system dynamically adjusts robot routes based on real-time environmental changes and detected human movements. The host management device continuously updates route plans by receiving image information from environmental cameras, detecting moving bodies, estimating their paths, and generating avoidance procedures. This dynamic adaptation resolves the contradiction by enabling operational efficiency improvement through real-time responsiveness while managing complexity through automated processing.
Solution Approach 2:
The system implements a feedback loop where environmental cameras continuously monitor the facility, detect moving bodies (people), estimate their paths, and feed this information back to the host management device. The device then generates avoidance procedures and updates robot routes accordingly. This closed-loop feedback mechanism enables the system to adapt to environmental changes and improve operational efficiency while maintaining manageable complexity through systematic information processing.
2Productivity
If multiple autonomous mobile robots operate simultaneously, then service coverage is improved, but interference with human movements increases due to more robots sharing the same space
Solution Approach 1:
The host management device acts as an intermediary that coordinates multiple autonomous mobile robots. It receives image information from environmental cameras, detects moving bodies, estimates their paths, and generates avoidance procedures that are distributed to relevant robots. This intermediary coordination enables multiple robots to operate simultaneously with improved service coverage while reducing interference with human movements through centralized path management.
Solution Approach 2:
The system replaces mechanical collision avoidance (physical sensors and reactive maneuvers) with optical detection and computational path planning. Environmental cameras capture image information that is processed by the host management device to detect moving bodies and estimate their paths. Avoidance procedures are generated computationally based on this information, allowing multiple robots to navigate human-populated spaces more smoothly and reduce interference.
3Adaptability or versatility
If real-time environmental monitoring is implemented, then route adaptability is improved, but system complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The environmental cameras serve multiple functions: they monitor the overall facility environment, detect moving bodies (people), provide image information for path estimation, and support avoidance procedure generation. This multi-functionality improves route adaptability by enabling real-time environmental monitoring while managing system complexity by using a single sensor type for multiple purposes rather than adding specialized sensors for each function.
Data Source
AI summary
To effectively enhance the operation efficiency of an autonomous mobile robot, an autonomous mobile robot control system includes a processor and a plurality of environmental cameras. The processor estimates a moving route of each of a plurality of moving bodies on the basis of characteristics of each of the plurality of moving bodies and sets a subset of the plurality of moving bodies whose moving routes overlap among the detected moving bodies as avoidance processing target moving bodies. The processor generates an avoidance procedure for the avoidance processing target moving bodies so the motion of the avoidance processing target moving bodies does not interfere with the motion of other avoidance target moving bodies.