Real-Time Object Pathing via Sensor Data
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Solution Overview
Problem
Current systems for generating pathing data for traveling objects in environments fail to effectively address collisions and congestion in real-time, leading to inefficiencies and potential blockages, as they do not utilize continuous, high-throughput sensor data to optimize paths dynamically.
Innovation Solution
A computer-implemented method that receives continuous real-time sensor data via a high-throughput communications network to determine environmental status, generate optimized pathing data for traveling objects, and output this data to associated computing devices, thereby avoiding collisions and congestion by altering paths in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current pathing systems are used without real-time sensor data, then system complexity is reduced, but collision detection and congestion avoidance capabilities deteriorate
Solution Approach 1:
The system performs preliminary actions by continuously collecting sensor data and pre-calculating potential collision risks and congestion points before objects actually encounter them. This allows the pathing system to proactively adjust trajectories, improving collision detection reliability while managing complexity through advance preparation rather than reactive complex computations.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from the environment is constantly monitored, analyzed for collision risks, and used to dynamically adjust pathing decisions. This feedback mechanism improves reliability by ensuring up-to-date collision detection while managing system complexity through efficient data processing and prioritization of critical information.
2Reliability
If real-time path optimization is implemented, then collision avoidance improves, but processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing computational resources on optimizing only the critical portions of paths that are likely to encounter congestion or collisions, rather than recalculating entire trajectories. This selective optimization improves congestion avoidance capability while reducing overall processing time by concentrating efforts on high-risk segments.
Solution Approach 2:
The system implements dynamic path optimization where the level and intensity of optimization adjustments vary based on real-time environmental conditions. When congestion or collision risks are detected, the system intensifies optimization efforts; when conditions are stable, it reduces processing intensity. This dynamic approach improves reliability when needed while minimizing average processing time.
3Manufacturing precision
If continuous sensor data processing is used, then pathing accuracy improves, but data transmission requirements and network bandwidth increase
Solution Approach 1:
The system extracts and processes only the essential and relevant features from continuous sensor data streams that directly impact pathing accuracy, such as object positions, velocities, and critical environmental obstacles. By filtering out redundant information and focusing on key parameters, the system maintains high pathing accuracy while significantly reducing the volume of data that needs to be transmitted across the network.
Solution Approach 2:
The system applies partial processing to sensor data by selectively analyzing only those data points and time intervals that are most relevant for accurate pathing decisions. Rather than processing every single sensor reading in full detail, the system focuses computational and transmission resources on critical data elements, maintaining pathing precision while reducing overall data transmission requirements.
Data Source
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AI summary
Embodiments of the disclosure provide for improved object pathing. The improved object pathing is provided based at least in part on continuous, real-time sensor data transmitted over a high-throughput communications network that enables updating of object in real-time as changes to an environment are detected from high-fidelity, continuous, real-time sensor data. Some embodiments are configured for receiving, in real-time via a high-throughput communications network, a continuous set of sensor data associated with one or more real-time sensors, determining current location data associated with at least one of a set of travelling objects within an environment, identifying current pathing data associated with each travelling object, generating optimized pathing data for the at least one travelling object based on the current pathing data and the current location data associated with each travelling object, and outputting the optimized pathing data to a computing device associated with the at least one travelling obj ect.