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
