DSP-SLAM++: A Unified Framework for Multi-Class, High-Fidelity Object SLAM in the Wild
Existing object-aware SLAM systems force a trade-off between real-time performance, multi-class support, and the generation of high-fidelity, semantically coherent object models. To address this trade-off, we present DSP-SLAM++, which extends the DSP-SLAM framework with an asynchronous mapping pipeline for real-time performance and dedicated sensor fusion adaptations for a monocular fisheye-LiDAR suite. Experiments demonstrate that our system generates fine-grained, geometrically-complete shapes for multiple object classes while eliminating severe mapping thread bottlenecks by reducing maximum object processing latency by up to 70\% compared to the state-of-the-art baseline, enabling robu...
| Authors | Ahmad Kourani, Ghina Daoud, Daniel Asmar et al. |
|---|---|
| Primary category | cs.RO |
| Published | 24 June 2026 |
| Last updated at source | 24 June 2026 |
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