Robotics and Autonomous Agents

Robots and Autonomous Agents

Robotic AI combines perception, planning, control schemes, and learning from demonstrations. Current systems utilize visual language models for instructions, world models for prediction, and hierarchical planning for complex tasks.

Perception includes 3D understanding, SLAM, object tracking, tactile

Applications include warehouse operations, manufacturing, logistics, domestic and service robots. Reliability management requires testing rare cases, sensor calibration, and fault recovery. Legally – responsibility, certification and standards.

live demo · related simulation● LIVE

The future is agents that learn throughout life, shared skills between p

Planning and control

Frequently asked questions

What are hierarchical planners, MPC and learning policies?

Hierarchical planners, MPC and learning policies for manipulation. Safe stops in case of uncertainty.

What is 3D reconstruction, visual language tools?

3D reconstruction, visual language instructions, integration of LiDAR and tactile sensors.

What is from demonstrations, reinforcement, offline-RL?

From demonstrations, reinforcement, offline-RL. Domain-randomized simulations for transfer to the real world.

What are metrics: task success, time execution, safety, recovery after failures.

Metrics: task success, execution time, safety, fault recovery.

▶ Try it live

Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Hash Function Avalanche Visualizer simulation