path-planning

This paper presents a conflict-free path-planning algorithm for en-route air traffic control, designed to be interpretable and computationally efficient for human operators. The algorithm integrates three conflict detection methods and achieves fast computation times, demonstrated on a real-world sector.

A paper proposing FLISP, a mapless path planning framework for cooperative UGV-UAV tunnel inspection using a single LiDAR-IMU suite, achieving 100% success rate and 7ms latency in a 1.2km tunnel.

DiffSlack proposes a differentiable projection layer that enforces nonlinear inequality constraints in neural networks by reformulating them as equalities with learnable slack variables, achieving improved feasibility and planning success in vehicle path planning.

This paper introduces DiffLNS, a hybrid framework integrating a discrete denoising diffusion probabilistic model (D3PM) with LNS2 for multi-agent path finding, using sparse social attention to generate warm-start plans. It achieves high success rates on complex and congested settings, outperforming baselines.