Kwangjin Yang

About

Kwangjin Yang is a leading researcher in autonomous robotics, specializing in motion planning and path smoothing for non-holonomic systems. His work addresses the critical challenge of generating feasible, smooth trajectories for robots with kinematic constraints operating in cluttered environments. Yang’s most influential contribution is the development of the Spline-Based RRT (Rapidly-exploring Random Tree) path planner, which integrates spline curves into the sampling-based planning framework to produce continuous curvature paths that respect vehicle dynamics. His seminal paper on this topic has garnered over 100 citations, establishing a foundational approach for non-holonomic robot navigation. To further refine trajectory quality, Yang introduced a continuous curvature path-smoothing algorithm using cubic Bézier spiral curves, which generates \(G^2\)-continuous paths that are both smooth and collision-free. This work, cited 48 times, proposes interactive and iterative algorithms that significantly enhance path smoothness over traditional piecewise linear methods. Additionally, his 2013 paper on efficient spline-based RRT planning in cluttered environments (30 citations) demonstrates how to simultaneously satisfy external obstacle constraints and internal kinematic limitations. Yang’s contributions are essential reading for researchers in field robotics and autonomous vehicle navigation.

Research Focus

Key Achievements

Top Papers

1. 1
   Spline-Based RRT Path Planner for Non-Holonomic Robots

   100 citations · 2013
2. 2
   Continuous curvature path-smoothing algorithm using cubic B zier spiral curves for non-holonomic robots

   48 citations · 2013
3. 3
   An efficient Spline-based RRT path planner for non-holonomic robots in cluttered environments

   30 citations · 2013

Key Collaborators

Contact & Links