Dynamic Hazard Escalation in Collaborative Mobile Robots
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Solution Overview
Problem
Dynamically stable robots pose hazards in collaborative environments due to unpredictable collapses and interactions with humans, making segregation strategies inefficient and unsafe, while conventional hazard mitigation methods are inadequate.
Innovation Solution
A mobile robot employs a variable hazard response strategy, including deceleration, reconfiguration, and safe operating stops based on real-time environmental data to mitigate risks, balancing efficiency and safety through escalating hazard mitigation features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dynamically stable robots are deployed in collaborative environments, then operational efficiency and task capability are improved, but safety hazards increase due to unpredictable collapses and interactions with humans
Solution Approach 1:
The patent implements a dynamic hazard response system that continuously adapts robot behavior based on real-time environmental assessment. The robot transitions between different operational modes (normal operation, hazard mitigation, safe operating stop) depending on detected conditions, allowing it to maintain high efficiency when safe while automatically prioritizing safety when hazards are present. This dynamic adaptation resolves the contradiction by making safety responses context-dependent rather than static.
Solution Approach 2:
The system employs continuous sensor feedback to monitor the collaborative environment for hazards. Detected hazard information feeds into a decision-making process that determines appropriate responses, creating a closed-loop control system. This feedback mechanism enables the robot to respond appropriately to actual conditions rather than following fixed safety protocols, resolving the contradiction between maintaining productivity and responding to real safety needs.
2Object-affected harmful factors
If conventional hazard mitigation methods are used, then safety is improved, but operational efficiency deteriorates due to segregation strategies
Solution Approach 1:
Instead of applying uniform safety restrictions throughout the entire collaborative environment, the patent implements localized hazard responses targeted at specific risk conditions. The robot assesses hazards locally and applies mitigation measures only when and where needed, rather than implementing blanket segregation strategies. This allows safe operation in high-risk zones while maintaining full productivity in low-risk areas, resolving the contradiction between safety and efficiency.
Solution Approach 2:
The system changes operational parameters dynamically based on hazard levels. When hazards are detected, parameters such as speed, operational mode, and safety responses are adjusted. When hazards are absent, parameters return to optimize productivity. This parameter adaptation allows the system to achieve high safety standards when needed while maintaining peak efficiency during normal operation, resolving the contradiction between safety and operational efficiency.
3Object-affected harmful factors
If escalating hazard response strategies are implemented, then safety is improved through real-time mitigation, but device complexity increases
Solution Approach 1:
The hazard response system is segmented into distinct functional modules: hazard detection sensors, hazard information processing, response determination logic, and executable mitigation actions. This modular segmentation allows each component to be independently developed, tested, and optimized, reducing overall system complexity while maintaining comprehensive safety functionality. The segmented architecture makes the complex safety system more manageable and easier to implement.
Data Source
AI summary
A method in accordance with at least some embodiments of the present technology includes determining first hazard information about a human in an environment at a first time. The method further includes decelerating a mobile robot in the environment based at least partially on the first hazard information. The method further includes determining second hazard information about the human at a second time after the first time. The method further includes reconfiguring the mobile robot based at least partially on the second hazard information. Reconfiguring the mobile robot includes moving the mobile robot from a standing configuration to a non-standing configuration. The method further includes determining third hazard information about the human at a third time after the second time. Finally, the method includes causing a safe operating stop of the mobile robot based at least partially on the third hazard information.