{"ID":2870276,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.12813","arxiv_id":"2509.12813","title":"Bridging Perception and Planning: Towards End-to-End Planning for Signal Temporal Logic Tasks","abstract":"We investigate the task and motion planning problem for Signal Temporal Logic (STL) specifications in robotics. Existing STL methods rely on pre-defined maps or mobility representations, which are ineffective in unstructured real-world environments. We propose the \\emph{Structured-MoE STL Planner} (\\textbf{S-MSP}), a differentiable framework that maps synchronized multi-view camera observations and an STL specification directly to a feasible trajectory. S-MSP integrates STL constraints within a unified pipeline, trained with a composite loss that combines trajectory reconstruction and STL robustness. A \\emph{structure-aware} Mixture-of-Experts (MoE) model enables horizon-aware specialization by projecting sub-tasks into temporally anchored embeddings. We evaluate S-MSP using a high-fidelity simulation of factory-logistics scenarios with temporally constrained tasks. Experiments show that S-MSP outperforms single-expert baselines in STL satisfaction and trajectory feasibility. A rule-based \\emph{safety filter} at inference improves physical executability without compromising logical correctness, showcasing the practicality of the approach.","short_abstract":"We investigate the task and motion planning problem for Signal Temporal Logic (STL) specifications in robotics. Existing STL methods rely on pre-defined maps or mobility representations, which are ineffective in unstructured real-world environments. We propose the \\emph{Structured-MoE STL Planner} (\\textbf{S-MSP}), a d...","url_abs":"https://arxiv.org/abs/2509.12813","url_pdf":"https://arxiv.org/pdf/2509.12813v2","authors":"[\"Bowen Ye\",\"Junyue Huang\",\"Yang Liu\",\"Xiaozhen Qiao\",\"Xiang Yin\"]","published":"2025-09-16T08:31:22Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"eess.SY\"]","methods":"[]","has_code":false}