Combining Bounding Boxes and JPS to Prune Grid Pathfinding
Authors: Steve Rabin, Nathan Sturtevant
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental results have two goals. The first is to illustrate the influence of the JPS canonical ordering on bounding boxes and to understand its overall performance. The second goal is to show how JPS+ with bounding boxes compares to state-of-the-art algorithms. We perform our primary comparison on a similar setup to the Grid-Based Path Planning Competition (Sturtevant 2014)... All experiments are performed on maps from the GPPC competition and the Moving AI map repository (Sturtevant 2012). |
| Researcher Affiliation | Academia | Steve Rabin Dept. of Computer Science Digi Pen Institute of Technology Redmond, WA, USA steve.rabin@gmail.com Nathan R. Sturtevant Dept. of Computer Science University of Denver Denver, CO, USA sturtevant@cs.du.edu |
| Pseudocode | Yes | Algorithm 1 describes the pre-computation. With a forward computation method and Dijkstra search, we must add an extra piece of information to be tracked by the Dijkstra search... Applying them to an A* search is straightforward and shown in Algorithm 2. |
| Open Source Code | No | The paper does not provide a statement or link indicating that the source code for the methodology is openly available. |
| Open Datasets | Yes | All experiments are performed on maps from the GPPC competition and the Moving AI map repository (Sturtevant 2012). |
| Dataset Splits | No | The paper does not explicitly provide specific train/validation/test dataset splits or mention cross-validation details for reproducibility. |
| Hardware Specification | Yes | We ran our code on the same server as the GPPC competition (a 2.4 GHz Intel Xeon E5620 with 12 GB of RAM), so timing comparisons against the GPPC competition are meaningful. |
| Software Dependencies | No | The paper does not provide specific version numbers for ancillary software components or libraries used in the experiments. |
| Experiment Setup | Yes | We perform our primary comparison on a similar setup to the Grid-Based Path Planning Competition (Sturtevant 2014)... All experiments are performed on maps from the GPPC competition and the Moving AI map repository (Sturtevant 2012). ...There are 347,868 problems in the entire set, and problems are run five times for statistical significance. Also, Algorithm 1 and 2 describe the core setup. |