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Explore the challenges and solutions in robot task planning through this JuliaCon 2024 talk. Delve into the complexities of orchestrating short-horizon motion plans into complex, goal-oriented tasks for robots. Examine how to effectively reason about knowledge bases with large ontologies but sparse data, particularly in scenarios like kitchen environments. Discover how Julia's multiple dispatch and metaprogramming capabilities are leveraged to implement efficient task planning systems. Learn about the development of a new task planning language designed to handle worlds described using large ontologies. Gain insights into the use of Julia packages such as Catlab.jl, AlgebraicRewriting.jl, and ACSets.jl in expressing and storing actions and world states for robotic task planning.
