Papers
2
Total Citations
9
H-Index
2
About
Hillol Das is a researcher at the forefront of mobile robotics and machine intelligence, specializing in sensor fusion, path optimization, and autonomous navigation in partially unknown environments. His work centers on developing bio-inspired algorithms that enable mobile agents to intelligently perceive and traverse complex spaces without relying on pre-mapped GPS data. Das’s most cited paper, “Noble Approach on Sensor Fused Bio Intelligent Path Optimisation and Single Stage Obstacle Recognition in Customized Mobile Agent” (2023, 7 citations), introduces a novel framework integrating SLAM-based sensor data with bio-intelligent optimization for point-to-point navigation and single-stage obstacle recognition. This work addresses a critical gap in real-time adaptive robotics. In a complementary study, “Geometric Representation of Obstacles Depth in a Partially Unknown Environment for Achieving Optimized Navigation by Mobile Robots” (2023, 2 citations), he proposes a geometric depth representation to enhance obstacle avoidance in dynamic settings. Though early in his career, Das’s contributions are already shaping how autonomous systems balance exploration and efficiency. His research holds promise for applications in search-and-rescue, warehouse automation, and field robotics, marking him as an emerging voice in intelligent navigation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2