Papers
1
Total Citations
9
H-Index
1
About
Isaac Asante’s research lies at the intersection of robotics, computer vision, and autonomous navigation, with a particular focus on enabling machines to perceive and interact with dynamic human environments. His most cited work, a 2023 study on segmentation-based angular position estimation, introduces a novel dynamic path planning method that fuses instance image segmentation with elementary matrix calculations. This approach allows a person-following robot to accurately identify the angular position of surrounding entities, integrating visual and depth data for robust scene understanding. With 9 citations already, this paper demonstrates Asante’s ability to craft computationally efficient solutions for real-world robotics challenges. His contributions are especially valuable for advancing human-robot interaction, where safe and responsive navigation is critical. Asante’s work stands out for its practical elegance—combining deep learning with geometric reasoning to solve a core problem in autonomous systems. For students and researchers exploring path planning or assistive robotics, his research offers a clear, implementable framework that bridges perception and action, marking him as an emerging voice in the field of intelligent mobile robots.
Research Focus
Key Achievements
Top Papers
- 1