Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing

• URL: http://arxiv.org/abs/2606.25754v1
• Date: Wed, 24 Jun 2026 12:23:00 GMT
• Title: Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing
• Abstract summary: This paper proposes a Stage-Aware and Roughness-Constrained Diffusion Policy (SRDP) for robotic polishing.<n>SRDP infers the process-stage posterior from multimodal observation histories and uses it to condition the shared reverse denoising process.<n>A roughness-oriented process-constrained diffusion sampling method is incorporated to generate constrained feed speed and normal contact force.
• Score: 5.400075443131777
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Polishing is a critical finishing process in high-end manufacturing fields such as aerospace, where surface quality directly affects the service performance and reliability of components. Robotic imitation learning provides a flexible solution for such tasks, but current methods remain limited in industrial polishing because of long-horizon dependencies, uncertain stage transitions, and the difficulty of modeling and regulating coupled process parameters. To address these issues, this paper proposes a Stage-Aware and Roughness-Constrained Diffusion Policy (SRDP) for robotic polishing. SRDP infers the process-stage posterior from multimodal observation histories and uses it to condition the shared reverse denoising process, enabling stage-consistent action generation without external stage labels during execution. Furthermore, a roughness-oriented process-constrained diffusion sampling method is incorporated to generate constrained feed speed and normal contact force under stage-wise preset spindle speeds, thereby improving process consistency and physical feasibility. Systematic experiments are conducted on two representative scenarios, namely spacecraft cabin coating-surface polishing and inner-cavity structural surface finishing. Comparisons with advanced baselines, ablation studies, and real-robot validations comprehensively evaluate the proposed method. The results show that SRD improves stage-transition stability, process-parameter consistency, and final surface quality across different polishing scenarios.

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