A comparative study of the performance of different search algorithms on FOON graphs

TL;DR

This paper compares the performance of BFS, GBFS with heuristics, and IDFS algorithms on FOON graphs to evaluate their effectiveness in robotic task planning.

Contribution

It provides a systematic comparison of search algorithms on FOON graphs, highlighting their strengths and weaknesses for robotic applications.

Findings

GBFS outperforms BFS and IDFS in certain scenarios

Heuristic functions improve search efficiency

IDFS is more memory-efficient but slower

Abstract

A robot finds it really hard to learn creatively and adapt to new unseen challenges. This is mainly because of the minimal information it has access to or experience towards. Paulius et al. [1] presented a way to construct functional graphs that encapsulate. Sakib et al. [2] further expanded FOON objects for robotic cooking. This paper presents a comparative study of Breadth First Search (BFS), Greedy Breadth First search (GBFS) with two heuristic functions, and Iterative Depth First Search (IDFS) and provides a comparison of their performance.