Sensor Fusion for Perception, World Understanding, and Intelligent Systems
A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Sensors and Robotics".
Deadline for manuscript submissions: 30 December 2026 | Viewed by 336
Editors
Interests: wireless sensor network; robotics; autonomous UAV
Interests: AI; image processing; image processing and computer vision; bioinformatics
Interests: mobile robotics; intelligent systems; self-driving cars; high-level control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Reliable perception and world understanding are foundational to intelligent systems operating in complex, dynamic, and resource-constrained real-world environments. Single sensing modalities often suffer from fundamental limitations such as sensitivity to environmental conditions, incomplete observability, and noise or failure under adverse scenarios. Current scholarship must address the following key challenges: (1) robust perception under uncertainty and sensor degradation caused by weather, occlusion, or partial failures; (2) real-time performance and deployment constraints where fusion must meet strict latency, energy, and compute budgets; and (3) cross-modal alignment issues including calibration, synchronization, and semantic compatibility across heterogeneous sensors.
This Special Issue calls for contributions that showcase advances in sensor fusion that integrate heterogeneous sensing modalities—such as vision, lidar, radar, inertial, acoustic, and emerging sensors—to overcome these challenges and enable robust perception, semantic world modeling, and intelligent decision-making.
Areas of interest include, but are not limited to, the following:
- Multi-modal perception and representation learning;
- Probabilistic, learning-based, and hybrid sensor fusion methods;
- Pose estimation and target tracking;
- Performance optimization for sensor fusion (latency, throughput, and energy efficiency);
- Real-time and edge-deployed fusion systems;
- Novel sensor development and experiments in industrial, medical, and agricultural applications;
- Cross-sensor calibration, synchronization, and self-supervised fusion;
- Theory and algorithms in world modeling and scene understanding;
- Experimental evaluation, benchmarking, and large-scale field studies;
- Sensor fusion for autonomous tasks (robotics, vehicles, UAVs, smart infrastructure);
- Fusion under uncertainty, sparsity, and adverse or degraded sensing conditions.
Dr. Ju Wang
Dr. Wei-Bang Chen
Prof. Dr. Alexander Ferrein
Guest Editors
Manuscript Submission Information
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Keywords
- sensor fusion
- multi-modal perception
- world modeling and understanding
- performance optimization
- experimental and real-world evaluation
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