SPADE: Sketch-guided Path Planning Augmented with Diffusion Experts
Path planning is essential for Autonomous Mobile Robots (AMRs). Conventional methods for incorporating human preferences into planning typically rely on either complex reward engineering or hardware-intensive solutions. Recent state-of-the-art frameworks leverage imitation learning to train behavior-specific path planning models from expert demonstrations. However, these approaches face two key limitations: limited generalization to unseen environments and low robustness in demonstration collection. To address these challenges, this work introduces an enhanced framework that focuses on two main contributions: an overhauled annotation tool built on ROS 2, and a novel training strategy that...
| Authors | Charbel Abi Hana, Tatiana Ghantous, Mikael Khalil et al. |
|---|---|
| Primary category | cs.RO |
| Published | 2 June 2026 |
| Last updated at source | 2 June 2026 |
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