2 papers
cs.RO2026
On Exploring Input Resolution Scaling For Anytime LiDAR Object Detection
Ahmet Soyyigit, Shuochao Yao, Heechul Yun
Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been shown to enhance the performance o…
cs.RO2024
TinyLidarNet: 2D LiDAR-based End-to-End Deep Learning Model for F1TENTH Autonomous Racing
Mohammed Misbah Zarrar, Qitao Weng, Bakhbyergyen Yerjan +2
Prior research has demonstrated the effectiveness of end-to-end deep learning for robotic navigation, where the control signals are directly derived from raw sensory data. However,…