AI RESEARCH
Seq-DeepIPC: Sequential Sensing for End-to-End Control in Legged Robot Navigation
arXiv CS.CV
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ArXi:2510.23057v2 Announce Type: replace-cross We present Seq-DeepIPC, a sequential end-to-end perception-to-control model for legged robot navigation in real-world environments. Seq-DeepIPC advances intelligent sensing for autonomous legged navigation by tightly integrating multi-modal perception (RGB-D + GNSS) with temporal fusion and control. The model jointly predicts semantic segmentation and depth estimation, giving richer spatial features for planning and control.