Aug 2026· 2026 IEEE International Conference on Mechatronics and Automation (ICMA)· pp. 493-498· 0 citations· 15 references
TL;DR
The method combines beam-wise barrier constraints with uncertainty-aware range-rate estimation from sequential LiDAR measurements and a predictive finite-horizon extension based on constant-input propagation to provide probabilistic safety guarantees at discrete sampling instants while preserving convexity and real-time tractability.
Abstract
This paper presents a discrete-time Perception-Aware Control Barrier Function (PA-CBF) framework for LiDAR-based robot navigation under uncertainty. The method combines beam-wise barrier constraints with uncertainty-aware range-rate estimation from sequential LiDAR measurements and a predictive finite-horizon extension based on constant-input propagation. The resulting safety filter provides probabilistic safety guarantees at discrete sampling instants while preserving convexity and real-time tractability. Simulation results show improved safety, smoother control, and higher task success than distance-only and reactive baselines in dynamic environments.
Autonomous navigation in previously unseen environments requires effective perception, persistent environmental representation, and collision avoidance while maintaining progress toward a goal. Existing perception-based methods often rely on prior maps or short-horizon observations, limiting their ability to exploit pr...
Jing-Shuo Li, Yi-Fan Xue, Yi-Fei Li et al.· 0 citations
The integration of LiDAR sensors into quadcopter control systems is fundamental for autonomous navigation in cluttered environments, yet the precise performance trade-offs between different tracking architectures under perceptual uncertainty remain insufficiently quantified. This paper presents a comprehensive 3D compu...
F. N. Murrieta-Rico, Gabriel Trujillo-Hernández, J. A. Amézquita García et al.· Applied Sciences· 0 citations
Control barrier functions (CBFs) provide a mathematically grounded framework for enforcing local collision-avoidance constraints in autonomous mobile robots, commonly through optimization-based safety filters. However, a minimum-intervention CBF filter lacks task-level maneuver awareness and may fail to select a produc...
Shi-Bo Li, Zhong-Cheng Wang, Jia-He Cao et al.· 0 citations
This work develops two new control barrier function (CBF) formulations: drift-measurement-robust (DMR)-CBFs and neural measurement-robust (NMR)-CBFs and provides theoretical analysis of the DMR-CBF along with numerical results on a planar double integrator and a 12D quadrotor.
Nicholas Rober, Yi-Xuan Jia, Jonathan P. How· 1 citation
Autonomous navigation in real-world public service, industrial inspection, and emergency response often faces frequent changes in nominally static scene structures, which can quickly invalidate pre-built global maps and naturally lead to a mapless navigation setting. We propose an end-to-end 3D LiDAR based navigation f...
Yue Zhai, Yan-Zi Miao· IEEE Robotics and Automation...· 0 citations
