Try possible actions and learn from the results of a new task.
Start with the task goal
Conceptual illustration. Implementation depends on the robot platform and task conditions.
THREE CONNECTED CAPABILITIES
From trying, to understanding, to improving.
01 / AUTONOMOUS EXPLORATION
Guided by the task. Driven by exploration.
Try actions, observe the results and find a viable path toward the task goal.
ACTION SPACE / CONCEPT
Option A
Task goal
Option B
Try
Action → feedback
Adjust
Explore candidate actions to find a feasible path
02 / VIRTUAL ↔ REAL
Connect virtual training with real-world feedback.
Explore strategies in simulation and refine them with real-world feedback.
SIM-TO-REAL / CONCEPT
Virtual training VIRTUAL
⇄
Real-world action REAL WORLD
Train · Act · Receive feedback · Refine
03 / CONTINUOUS IMPROVEMENT
Turn practical experience into the next improvement.
Use experience after deployment to guide improvement and reduce repeated tuning.
ITERATION / CONCEPT
Illustrative iterations, not measured performance or a growth guarantee
Self-evolving capabilities must be designed alongside robot hardware, task goals, operating constraints, and evaluation methods. Specific capabilities and outcomes need validation in a defined setting; a single algorithm or general demo cannot establish them.
From a learning loop to a real-world task.
Explore how autonomous learning could respond to variation within concrete tasks.