Task Tree Retrieval for Robotic Cooking
This work addresses the challenge of improving robotic efficiency and reliability in kitchen tasks, but it appears incremental as it builds on existing knowledge representation methods.
The paper tackles the problem of robotic cooking by introducing FOON, a structural knowledge representation based on human manipulations, and implements three algorithms with weighted values to reduce failure rates and ensure effective task completion.
Robotics is used to foster creativity. Humans can perform jobs in their unique manner, depending on the circumstances. This situation applies to food cooking. Robotic technology in the kitchen can speed up the process and reduce its workload. However, the potential of robotics in the kitchen is still unrealized. In this essay, the idea of FOON, a structural knowledge representation built on insights from human manipulations, is introduced. To reduce the failure rate and ensure that the task is effectively completed, three different algorithms have been implemented where weighted values have been assigned to the manipulations depending on the success rates of motion. This knowledge representation was created using videos of open-sourced recipes