Robot Task Planning

Robot Task Planning
Methods used to select sequences of robot actions to achieve goals under constraints.
Area	Physical AI and robotics
Applications	Research, engineering and systems operation

Robot Task Planning methods used to select sequences of robot actions to achieve goals under constraints.

Planning levels

High-level task planners may choose operations such as navigating, retrieving and placing an object. Motion planners decide trajectories that respect geometric or dynamic constraints. Some systems also use reactive controllers for immediate feedback.

Representations

Plans may use symbolic preconditions, state machines, behavior trees, optimization methods or learned policies. Each representation has different strengths for explainability, responsiveness and runtime verification.

Connection to language models

A language-capable model can propose a sequence of tasks, but it still requires grounding in real sensors and checking whether the actions are permitted and physically feasible.

Failure handling

Practical planners need conditions for retry, human intervention and safe termination. Uncertain observations and changing obstacles can invalidate an otherwise logical plan.

See also

• Autonomous Navigation
• Vision-Language-Action Models
• Robot Safety Risk Assessment

Further reading

• RT-2: New model translates vision and language into action — Google DeepMind
• AI Risk Management Framework (AI RMF 1.0) — NIST