CMP-IRRT*: A Perception-Assisted Height-Adaptive Planner for Quadruped Robots

cs.RO

Submitted: 2026-10-07

Updated: 2026-10-07

Comments: Accepted at the 18th Asian Conference on Machine Learning (ACML 2026)

Code: https://github.com/MingfanZhao/height-adaptive-planner

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• YOLOv11: An Overview of the Key Architectural Enhancements
• Depth Anything V2
• Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Related papers

• FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
• ARC: A Reasoning Recipe for Robot Foundation Models
• HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies