Physical AI Workbench

Latent Trajectory Diffusion & Action Quantization

PHYSICS ENVIRONMENT

Drag target keypoint 🎯 or obstacles to steer latent trajectory. Click "Run Trajectory Execution" to execute.

Latent Spatial Diffusion Planner

Denoising Steps 20

Guidance Scale (ω) 2.5

Continuous Action Quantization Motor Execution

Joint Precision Depth 8-bit INT8

Closed-Loop RL Fine-Tuning Policy Adapt

Fine-Tune Episodes 50

Execution Telemetry Live Gauges

Trajectory Error 12.4 mm

Motor Torque Chatter 4.8 Nm

Task Success Rate 88%

Policy Divergence 0.042

Latent Robotics Diffusion & Action Quantization Summary

Closed-loop physical AI validation demonstrates how continuous action quantization precision directly dictates joint chatter and position drift under spatial diffusion trajectories.

Preset Environment: Obstacle Navigation

Denoising Steps: 20

Action Quantization: 8-bit INT8

Calculated Trajectory Error: 12.4 mm

Observed Torque Chatter: 4.8 Nm

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