Practical AI Solutions for Contact-Rich Manipulation Tasks
TRANSIC: A Human-in-the-Loop Method
Researchers at Stanford University have proposed TRANSIC, a method to handle the sim-to-real transfer of policies for contact-rich manipulation tasks. This approach integrates a good base policy learned from simulation with limited real-world data, efficiently using human correction data to address the sim-to-real gap.
Key Steps to Evolve Your Company with AI
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
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