Intelligent Perception and Safe Navigation Control for Autonomous Unmanned Systems in Complex Environments

Autonomous unmanned systems are increasingly deployed in aerial, ground, surface, and underwater operations, where they are expected to perform reliably in dynamic, uncertain, and safety-critical environments. Applications such as disaster response, infrastructure inspection, environmental monitoring, intelligent transportation, and industrial operations require unmanned platforms to perceive complex surroundings, interpret evolving situations, and generate safe navigation and control actions in real time. In recent years, rapid progress in sensing, artificial intelligence, and control theory has significantly improved autonomy. However, major challenges remain in robust perception under noise and occlusion, safe navigation in cluttered and changing environments, resilience to disturbances and communication constraints, and the integration of learning-based methods with dependable control architectures. These challenges make intelligent perception and safe navigation control a central research theme for the next generation of autonomous unmanned systems.This Research Topic aims to gather recent advances that strengthen the connection between perception, decision-making, and safe navigation control for autonomous unmanned systems operating in complex environments. The goal is to highlight approaches that do not treat sensing and control as isolated modules, but instead develop integrated frameworks in which environmental understanding directly informs motion planning, trajectory generation, obstacle avoidance, and closed-loop control. We are particularly interested in contributions that address safety, robustness, adaptability, and real-time performance under uncertainty. Relevant studies may focus on perception-aware control, risk-aware navigation, disturbance rejection, resilient autonomy, or distributed coordination among multiple unmanned agents. This Topic also seeks to encourage research that bridges theory and practice, including algorithmic innovation, benchmark development, simulation-to-real transfer, and field validation. By bringing together researchers from robotics, artificial intelligence, autonomous systems, and control engineering, this collection aims to advance intelligent unmanned platforms capable of operating safely, efficiently, and autonomously in challenging real-world scenarios.This Research Topic welcomes contributions on, but not limited to, the following themes:· multimodal sensing and environment perception for unmanned systems; localization, mapping, and state estimation in complex environments; · perception-driven motion planning and trajectory tracking; safe navigation and obstacle avoidance; · adaptive, robust, and learning-based control; risk-aware and constraint-aware decision-making; · cooperative perception and distributed navigation control for multi-agent systems; · resilient autonomy under disturbances, limited communication, or incomplete observations;· simulation-to-real transfer; · datasets, benchmarks, and real-world experiments for autonomous unmanned platforms. Submissions concerning aerial, ground, surface, underwater, or heterogeneous unmanned systems are all encouraged. Authors are invited to submit Original Research and related article types supported by the journal. Contributions may emphasize theoretical methods, algorithm development, system integration, or experimental validation, provided they clearly advance intelligent perception and safe navigation control for autonomous unmanned systems. Topic editors: Xiaojie Sun, Guohua Wu, Pengcheng Liu, Yang Cao Source: https://www.frontiersin.org/research-topics/79554/intelligent-perception-and-safe-navigation-control-for-autonomous-unmanned-systems-in-complex-environments