Combining Task and Motion Planning: Challenges and Guidelines

Area of Science:

• Robotics and Artificial Intelligence
• Algorithmic Decision-Making

Background:

• Combined Task and Motion Planning (TAMP) lacks a universal solution.
• Domain specifics and operational needs heavily influence TAMP algorithm and representation design.
• Effective TAMP systems often require careful consideration of trade-offs.

Purpose of the Study:

• To address the need for adaptable TAMP solutions.
• To propose five key research questions for advancing TAMP.
• To provide a guideline for designing effective TAMP systems for specific scenarios.

Main Methods:

• Formulating five critical research questions for TAMP.
• Analyzing design decisions and trade-offs related to these questions.
• Illustrating concepts with examples from existing application domains.

Main Results:

• Identification of five research questions crucial for real-world TAMP.
• A framework for understanding and making design trade-offs in TAMP.
• Demonstration of how to tailor TAMP solutions to specific application needs.

Conclusions:

• A structured approach is necessary for effective TAMP system design.
• Addressing the proposed research questions will facilitate practical TAMP solutions.
• This work offers a valuable guideline for researchers and practitioners in the TAMP field.