AGV Human Interaction and Collision Avoidance
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Solution Overview
Problem
Existing automatic guided vehicles (AGVs) lack the ability to effectively interact with human operators and avoid collisions during operation, limiting their functionality and safety in dynamic environments.
Innovation Solution
The development of AGVs equipped with a mobile base, console, cameras, and sensors that allow them to switch between self-navigating, leading, and following modes, enabling interaction with human operators and collision avoidance through image and gesture recognition, and communication via a warehouse management system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AGVs operate in traditional autonomous modes only, then navigation efficiency is maintained, but interaction capability with human operators deteriorates
Solution Approach 1:
The AGV system implements multiple operational modes (autonomous navigation mode, following mode, leading mode) within a single platform. The controller can switch between these modes based on operational requirements, allowing the AGV to serve both autonomous transport functions and human interaction functions. This multi-functionality resolves the contradiction by enabling the system to adapt to different operational contexts without requiring separate specialized vehicles.
Solution Approach 2:
The AGV system dynamically switches between different operational modes (autonomous, following, leading) based on real-time operational needs and human operator presence. The camera system continuously monitors for human operators, and the controller adjusts the navigation mode accordingly. This dynamic adaptability allows the system to maintain optimal performance while providing versatile interaction capabilities when needed.
2Productivity
If AGVs move at high speed, then productivity is improved, but collision risk with human operators increases
Solution Approach 1:
The camera system continuously monitors the environment for human operators and provides real-time feedback to the controller. When a human operator is detected, the controller receives feedback and automatically adjusts the AGV's speed and navigation mode to prevent collisions. This feedback loop enables the system to maintain high productivity during autonomous operation while ensuring safety when human operators are present.
Solution Approach 2:
The system takes preliminary action by continuously scanning for human operators before potential collision scenarios develop. The camera system proactively identifies human presence in the operational area, and the controller pre-adjusts speed and mode before any collision risk materializes. This preliminary detection and response mechanism prevents collisions while allowing the AGV to maintain efficient transport speeds during safe autonomous operation.
3Adaptability or versatility
If AGVs use fixed navigation routes, then operational reliability is maintained, but flexibility in responding to human operators deteriorates
Solution Approach 1:
The navigation system dynamically adjusts between fixed route following and adaptive path planning based on detected human operator presence. In autonomous mode, the AGV follows predetermined routes for reliable efficient operation. When human operators are detected via the camera system, the controller dynamically switches to following or leading modes, adapting the navigation path in real-time. This dynamic control approach provides flexibility without requiring complete abandonment of structured navigation.
Solution Approach 2:
The navigation system is segmented into distinct operational modes (autonomous navigation, following, leading) that can be independently controlled and switched between. Each mode has its own control logic and navigation approach. This segmentation allows the system to maintain reliable fixed route navigation during autonomous operation while providing flexible human-responsive modes when needed, without requiring the entire navigation system to be simultaneously complex.
Data Source
AI summary
Embodiments of the present disclosure relate to automatic guide vehicles (AGVs) that are capable of interacting with human operators. Particularly, the AGVs can follow a human operator, lead a human operator, and receive and react to gestures from a human operator. The AGVs switches directions of moving to provide human operators with easy access to components of user interface on the AGVs. The AGVs are also capable of avoiding collision with other AGVs by yielding to AGVs with a higher priority level.