3 papers
cs.RO2024
A POMDP-based hierarchical planning framework for manipulation under pose uncertainty
Muhammad Suhail Saleem, Rishi Veerapaneni, Maxim Likhachev
Robots often face challenges in domestic environments where visual feedback is ineffective, such as retrieving objects obstructed by occlusions or finding a light switch in the dar…
cs.MA2024
Work Smarter Not Harder: Simple Imitation Learning with CS-PIBT Outperforms Large Scale Imitation Learning for MAPF
Rishi Veerapaneni, Arthur Jakobsson, Kevin Ren +3
Multi-Agent Path Finding (MAPF) is the problem of effectively finding efficient collision-free paths for a group of agents in a shared workspace. The MAPF community has largely foc…
cs.RO2024
A Data Efficient Framework for Learning Local Heuristics
Rishi Veerapaneni, Jonathan Park, Muhammad Suhail Saleem +1
With the advent of machine learning, there have been several recent attempts to learn effective and generalizable heuristics. Local Heuristic A* (LoHA*) is one recent method that i…