Muhammad Wisal
Papers
1
Total Citations
2
H-Index
1
About
Muhammad Wisal is a researcher specializing in visual simultaneous localization and mapping (vSLAM) and robotic perception, with a particular focus on enhancing system robustness in dynamic environments. His most notable contribution, "CA-SLAM: Contour-Aware SLAM System Based on RGB-D Sensors in Dynamic Environment" (2025), addresses a critical challenge in vSLAM—the degradation of accuracy caused by moving objects. By introducing a contour-aware approach that leverages RGB-D sensors, Wisal's work improves the reliability of SLAM systems in real-world, unpredictable settings, a key step toward practical deployment in autonomous navigation and augmented reality. Though early in its citation impact, this work has already garnered attention for its innovative methodology. Wisal's research bridges the gap between theoretical SLAM algorithms and real-world applicability, offering solutions that are both computationally efficient and robust. His contributions are particularly valuable for students and researchers exploring the intersection of computer vision, robotics, and sensor fusion, as they demonstrate how targeted algorithmic design can overcome long-standing limitations in dynamic scene understanding.
Research Focus
Key Achievements
Top Papers
- 1