Browser Teleop Fleet Lab: Latency & Kinematic Feedback Simulator

Teleop Scenario Preset

Network Latency 250 ms

Jitter Variance 30 ms

Packet Drop Rate 1.0%

Control Feedback Mode

Raw Uncompensated

Direct delayed open-loop commands

Predictive Dead Reckoning

Local shadow state trajectory estimate

Closed-Loop PID Guidance

Autonomous target vector trajectory

Teleop Drive Control [WASD / Touch]

Actual Physical Robot Local Intent (Ghost) Goal Waypoints

Teleop Link Active

Target Waypoints: 0 / 3 Completed

Drift Error Vector

4.2 cm

Packet Buffer Queue

6 pkts

Command RTT

280 ms

Stability Score

92.4%

Wheel Velocity L / R 0.0 / 0.0 rad/s

LIDAR Ray Sweeps 30 Hz

Actual Robot Pos: X: 100, Y: 100

Ghost Target Pos: X: 100, Y: 100

Obstacle Collisions: 0

Elapsed Sim Time: 18.5 s

When controlling physical AI mobile robots via web protocols, delayed network packets cause overshooting and control loop instability.

Dead Reckoning locally simulates kinematic motion equations to give immediate feedback before network round-trips resolve.

Teleop Trial Benchmark ACTIVE

Target circuit loaded with 250ms buffer lag. Move the robot using WASD/joystick to hit target waypoints and generate control benchmark.