HAN Humanoid Navigation Transformer v1

Overview

This model is designed for humanoid robot navigation and path planning. It predicts optimal movement directions based on multi-sensor input.

The model focuses on indoor navigation with obstacle avoidance.

Architecture

  • Transformer Encoder
  • 6 Layers
  • 8 Attention Heads
  • Hidden Size: 512
  • Feedforward Size: 2048
  • Activation: GELU

Observation Space

  • Depth sensor input
  • IMU orientation
  • Distance sensors
  • Velocity vectors

Action Space

  • Forward movement
  • Turning angle
  • Step length adjustment

Training Data

  • Simulated indoor navigation environments
  • Random obstacle layouts
  • Dynamic object movement scenarios

Intended Use

  • Humanoid navigation research
  • Robotics simulation projects
  • Indoor autonomous movement

Limitations

Trained in simulation. Real-world deployment requires domain adaptation.

Author

Caplin43

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