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[Reproducibility Report] Path Planning using Neural A* Search

arXiv 2208.04153 ↗First posted 16 Jul 2022cs.AIcited by 0

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Abstract (arXiv)

The following paper is a reproducibility report for "Path Planning using Neural A* Search" published in ICML2 2021 as part of the ML Reproducibility Challenge 2021. The original paper proposes the Neural A* planner, and claims it achieves an optimal balance between the reduction of node expansions and path accuracy. We verify this claim by reimplementing the model in a different framework and reproduce the data published in the original paper. We have also provided a code-flow diagram to aid comprehension of the code structure. As extensions to the original paper, we explore the effects of (1) generalizing the model by training it on a shuffled dataset, (2) introducing dropout, (3) implementing empirically chosen hyperparameters as trainable parameters in the model, (4) altering the network model to Generative Adversarial Networks (GANs) to introduce stochasticity, (5) modifying the encoder from Unet to Unet++, (6) incorporating cost maps obtained from the Neural A* module in other variations of A* search.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 30 references that are in the map. First posted on arXiv 16 Jul 2022.

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19 of 30 references.

References · 19

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  9. 2016Value Iteration Networkscited by 160
  10. 2018Motion Planning Networkscited by 80
  11. 2020Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Datacited by 58
  12. 2020A Framework For Contrastive Self-Supervised Learning And Designing A New Approachcited by 52
7 more
  1. 2020Path Planning using Neural A* Searchcited by 52
  2. 2017Data-driven Planning via Imitation Learningcited by 36
  3. 2017Learning Heuristic Search via Imitationcited by 34
  4. 2018Gated Path Planning Networkscited by 31
  5. 2019LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Netcited by 5
  6. 2020Efficient Heuristic Generation for Robot Path Planning with Recurrent Generative Modelcited by 4
  7. 2021Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentationcited by 1

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