Lokeshkumar Malke
Papers
1
Total Citations
38
H-Index
1
About
Lokeshkumar Malke is a researcher at the forefront of autonomous mobile robotics, with a specialized focus on enabling robots to navigate complex, human-centric environments. His work centers on the critical challenge of stair detection and traversal, a fundamental capability for robots deployed in urban search and rescue, surveillance, and industrial inspection. Malke’s most cited contribution, "Deep Learning Based Stair Detection and Statistical Image Filtering for Autonomous Stair Climbing" (2019), has garnered 38 citations, demonstrating its influence in the field. In this seminal paper, he pioneered a hybrid approach that combines deep learning for robust stair recognition with statistical image filtering to enhance detection accuracy under varied lighting and surface conditions. This work directly addresses a key bottleneck in mobile robotics, moving beyond traditional geometric methods to achieve more reliable autonomous stair climbing. By bridging computer vision and control systems, Malke’s research provides a practical pathway for deploying robots in multi-level terrains, significantly advancing the safety and autonomy of mobile platforms in unstructured, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1