Papers
1
Total Citations
4
H-Index
1
About
Jyotish is a researcher in robotics and autonomous systems, with a primary focus on real-time path planning and motion control for nonholonomic mobile robots. Their key contributions lie in developing computationally efficient algorithms that enable robots to navigate dynamic, unpredictable environments. In their most-cited work, "A TD-RRT* Based Real-Time Path Planning of a Nonholonomic Mobile Robot and Path Smoothening Technique Using Catmull-Rom Interpolation" (2022), Jyotish introduced a time-dependent Rapidly-exploring Random Tree Star (TD-RRT*) approach that adapts to moving obstacles, combined with Catmull-Rom interpolation for generating smooth, feasible trajectories. This work addresses a critical challenge in robotics: bridging the gap between theoretical planning and real-world deployment where environments are rarely static. With 4 citations, this paper has already influenced subsequent research in adaptive path planning. Jyotish’s work is particularly valuable for applications in autonomous vehicles, warehouse robotics, and service robots operating in human-centric spaces. Their research demonstrates a strong commitment to practical, implementable solutions that push the boundaries of real-time robotic navigation.
Research Focus
Key Achievements
Top Papers
- 1