Distributed Simulation Object Rendering via Predictive Velocity Adjustment
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Solution Overview
Problem
Distributed interactive simulations face challenges in presenting realistic and smooth motion of remotely managed objects due to latency and bandwidth constraints, leading to jerky or unpredictable behavior, especially in simulations requiring precise targeting and tracking.
Innovation Solution
A method that involves predicting the status of remotely managed objects by adjusting velocities and parameters based on discrepancies between predicted and actual states, using threshold values specific to object types, to render a more aesthetically pleasing and realistic visual representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If updates are distributed frequently to all stations, then the visual presentation becomes smoother and more realistic, but network bandwidth consumption increases and latency problems worsen
Solution Approach 1:
The patent applies local quality by sending high-frequency updates only to the controlling station while providing low-frequency updates to remote stations. Each station receives updates at a frequency appropriate to its specific needs - the controlling station gets complete detailed updates for precise object management, while remote stations receive sufficient updates to maintain visual coherence without excessive bandwidth consumption.
Solution Approach 2:
The system dynamically adjusts update frequencies based on the station's role and the object's importance. Update rates are not fixed but adapt according to whether the station is controlling or observing, and whether the object is critical to the simulation. This dynamic approach optimizes bandwidth usage while maintaining visual quality where needed.
2Loss of energy
If updates are sent less frequently to save bandwidth, then network efficiency improves, but the visual presentation becomes jerky and unrealistic
Solution Approach 1:
Different update frequencies are applied locally at different stations based on their specific requirements. Controlling stations receive high-frequency updates to maintain precise control and accurate object representation, while remote stations receive lower-frequency updates that are sufficient for visual coherence. This local differentiation resolves the contradiction by optimizing bandwidth efficiency without sacrificing visual quality where it matters most.
3Reliability
If detailed models are computed at all stations, then each station has complete information for accurate simulation, but computational complexity and processing requirements increase significantly
Solution Approach 1:
The patent merges the detailed computational model with the controlling station, eliminating the need for duplicate detailed models at remote stations. The controlling station maintains the authoritative detailed model and computes all complex simulations centrally, then distributes results to remote stations. This consolidation reduces overall computational complexity while maintaining simulation accuracy through centralized model management.
Solution Approach 2:
Remote stations receive simplified copies or representations of object states rather than full detailed models. Instead of each station maintaining complete detailed models, the system uses centralized model computation with distributed result distribution. This copying approach maintains reliability by ensuring all stations have access to accurate object state information while dramatically reducing computational complexity at individual stations.
4Speed
If the simulation runs at high update rates, then the simulation becomes more realistic and responsive, but network latency and update distribution delays become more problematic
Solution Approach 1:
The patent applies local quality by allowing the controlling station to run at high update rates without being constrained by network latency to itself. The controlling station processes updates locally with minimal delay, maintaining high simulation speed and responsiveness. Remote stations operate at lower effective update rates determined by network update frequency, which is sufficient for visual coherence. This local differentiation resolves the latency problem by maximizing speed where it matters most (controlling station) while accepting lower rates where network delays are unavoidable (remote stations).
Data Source
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AI summary
Systems and methods for substantially contemporaneously presenting a distributed simulation at multiple computing devices. A first computing device controls an object in the simulation. A second computing device generates a visual representation of the object associated with a visual status. The second computing device generates a predicted status and receives an update including new status from the first computing device. A portion of the predicted status is set equal to a portion of the new status, and a discrepancy between the predicted and visual statuses is determined. When the discrepancy is greater than a first threshold, at least one velocity of the predicted status may be modified. When the discrepancy is greater than a second threshold, the visual status is modified based at least in part on the predicted status. A new visual representation of the object is rendered based at least in part on the visual status, and displayed.