Parth Joshi
Papers
1
Total Citations
7
H-Index
1
About
Parth Joshi is a pioneering researcher in the field of swarm robotics and motion planning, with a particular focus on controlling large groups of microrobots using global inputs. His most-cited work, "Motion-planning Using RRTs for a Swarm of Robots Controlled by Global Inputs" (2019, 7 citations), addresses a fundamental challenge in medical and micro-assembly applications: how to steer multiple small-scale robots when they all receive the same control signal, such as the uniform magnetic gradient from an MRI scanner. Joshi's key contribution lies in adapting Rapidly-exploring Random Trees (RRTs) to solve motion planning problems for robot swarms under these constraints, enabling precise navigation of individual robots despite identical global inputs. This work has significant implications for targeted drug delivery, minimally invasive surgery, and micro-manufacturing. While still early in his career, Joshi's research bridges the gap between theoretical robotics and practical biomedical applications, offering elegant solutions to the unique constraints of small-scale robotic systems. His work continues to inspire new approaches to controlling multi-agent systems in challenging environments.
Research Focus
Key Achievements
Top Papers
- 1