9 citations · 28 across the 5 of their papers we have counts for
5 papers
A-MHA*: Anytime Multi-Heuristic A*
Ramkumar Natarajan, Muhammad Suhail Saleem, William Xiao +3
Designing good heuristic functions for graph search requires adequate domain knowledge. It is often easy to design heuristics that perform well and correlate with the underlying tr…
ePA*SE: Edge-based Parallel A* for Slow Evaluations
Shohin Mukherjee, Sandip Aine, Maxim Likhachev
Parallel search algorithms harness the multithreading capability of modern processors to achieve faster planning. One such algorithm is PA*SE (Parallel A* for Slow Expansions), whi…
MPLP: Massively Parallelized Lazy Planning
Shohin Mukherjee, Sandip Aine, Maxim Likhachev
Lazy search algorithms have been developed to efficiently solve planning problems in domains where the computational effort is dominated by the cost of edge evaluation. The existin…
Euclidean Distance-Optimal Post-Processing of Grid-Based Paths
Guru Koushik Senthil Kumar, Sandip Aine, Maxim Likhachev
Paths planned over grids can often be suboptimal in an Euclidean space and contain a large number of unnecessary turns. Consequently, researchers have looked into post-processing t…
Learning Optimal Decision Making for an Industrial Truck Unloading Robot using Minimal Simulator Runs
Manash Pratim Das, Anirudh Vemula, Mayank Pathak +2
Consider a truck filled with boxes of varying size and unknown mass and an industrial robot with end-effectors that can unload multiple boxes from any reachable location. In this w…