Phase 2: Asimov Agent 1.0

Objective: Expand functionality with adaptive and dynamic capabilities.

• Feature Enhancements:

  • Dynamic Environment Mapping: Allow users to define custom terrains and challenges, with real-time feedback on robot performance.

  • Adaptive Learning: Integrate reinforcement learning models that adjust robot behavior based on training outcomes and dynamic changes in the environment.

  • Interactive Visual Tools: Enable users to manipulate robotic designs visually while receiving live performance analytics.

• Implementation Challenges:

  • Domain randomization for robust Sim2Real transfer.

  • Multi-modal training data integration (visual, tactile, and sensor inputs).