Federated Control for Autonomous Building Navigation
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Solution Overview
Problem
Current autonomous systems for navigation, such as drones and robots, face limitations in navigating within buildings and adapting to changing conditions, relying on centralized servers for control and relying on human oversight for tasks like delivery, which reduces adaptability and efficiency.
Innovation Solution
A federated automated interoperation system that allows autonomous devices to interact with cloud services and smart premises, using beacons and building infrastructure services for localized control and management, enabling dynamic adaptation to internal building structures and conditions through distributed interoperation and just-in-time knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If centralized server control is used for autonomous devices, then coordination and management are simplified, but adaptability to changing conditions and loss of connection resilience deteriorate
Solution Approach 1:
The control system is segmented into multiple independent components: autonomous devices maintain local decision-making capabilities while connecting to optional centralized coordination services. Each device operates autonomously with its own navigation and task execution systems, allowing the system to function even when centralized coordination is unavailable or disconnected.
Solution Approach 2:
The control architecture transitions from static centralized control to dynamic distributed control. Autonomous devices can dynamically adjust their operational mode based on connection availability, switching between coordinated operation when connected and independent autonomous operation when disconnected, enabling continuous task completion regardless of communication status.
2Ease of manufacture
If centralized server control is used for autonomous devices, then initial route planning is simplified, but real-time adaptability to changing conditions deteriorates
Solution Approach 1:
Initial route planning and task coordination are performed in advance by centralized services when conditions permit, preparing navigation paths and task sequences before autonomous devices depart. This preliminary preparation simplifies the overall planning process while allowing real-time adjustments during execution through on-device decision-making capabilities.
Solution Approach 2:
Autonomous devices possess self-service capabilities for real-time navigation and task execution without requiring continuous centralized guidance. Each device independently processes sensor data, navigates obstacles, and adapts to changing conditions using onboard intelligence, eliminating the need for constant server intervention while maintaining ease of initial planning through centralized service preparation.
3Reliability
If human oversight is required for autonomous delivery, then safety and control are improved, but operational efficiency and autonomy deteriorate
Solution Approach 1:
Autonomous devices perform self-service for navigation, obstacle avoidance, and task execution without requiring human operators. The systems independently process environmental sensors, make navigation decisions, and complete delivery tasks autonomously, dramatically improving operational efficiency while maintaining safety through robust onboard safety systems and contingency protocols.
Solution Approach 2:
Autonomous devices continuously monitor their operational status, environmental conditions, and task progress through sensor feedback loops. This real-time feedback enables automatic safety responses, collision avoidance, and task completion verification without human intervention, maintaining high safety standards while achieving full operational autonomy and maximum productivity.
4Ease of operation
If autonomous devices navigate using pre-mapped routes, then navigation simplicity is improved, but adaptability to changing building conditions deteriorates
Solution Approach 1:
Building maps and navigation routes are prepared in advance through preliminary mapping operations, providing autonomous devices with pre-established navigation paths and building layout information. This preliminary preparation simplifies navigation planning while allowing real-time adaptability through onboard sensors that detect and respond to changing conditions such as temporary obstacles or closed passages during actual traversal.
Solution Approach 2:
The navigation system transitions from static pre-mapped routes to dynamic adaptive navigation. Autonomous devices use onboard sensors to detect real-time environmental changes and dynamically adjust their paths while maintaining overall mission objectives. The system combines pre-planned routes with real-time sensor-based navigation, enabling both navigation simplicity through pre-mapping and adaptability to changing conditions through dynamic path adjustment.
Data Source
AI summary
In some embodiments, the disclosed subject matter involves communication and negotiation between an autonomous entity or vehicle with a network of communication resources within a smart premises. The communication resources may include entry, landing or navigation beacons and a building infrastructure service. Negotiation for guidance, entry and other authorized tasks or services may be performed in a distributed fashion while en route or in proximity to a communication resource, rather than scheduled by a centralized server. Other embodiments are described and claimed.