Songchang Jin

About

Songchang Jin is a rising researcher in robotics, specializing in coverage path planning (CPP) for multi-robot systems and curvature-constrained vehicles. His work addresses fundamental challenges in autonomous navigation, including the coordination of multiple Dubins robots for efficient area coverage—critical for applications in aerial monitoring, marine exploration, and search and rescue. Jin’s most cited paper, "Exact and Heuristic Multi-Robot Dubins Coverage Path Planning for Known Environments" (2023, 44 citations), introduces novel algorithms that balance exactness and heuristic efficiency, significantly advancing multi-robot coverage path planning (MCPP). He has also tackled the complexities of variable-speed robots and obstacle avoidance, as seen in his 2023 work on collision-free CPP for curvature-constrained robots. Notably, his 2022 paper on complete coverage with robots of different velocities (11 citations) addresses the practical challenge of heterogeneous robot teams, while his 2025 work on hierarchy coverage with proactive extremum prevention pushes online CPP forward. With a growing citation record and contributions to both exact and heuristic methods, Jin is shaping the future of autonomous coverage in unknown and dynamic environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Exact and Heuristic Multi-Robot Dubins Coverage Path Planning for Known Environments

   44 citations · 2023
2. 2
   Complete coverage problem of multiple robots with different velocities

   11 citations · 2022
3. 3
   SP2E: Online Spiral Coverage with Proactive Prevention Extremum for Unknown Environments

   10 citations · 2023
4. 4
   Collision-free Coverage Path Planning for the Variable-speed Curvature-constrained Robot

   4 citations · 2023
5. 5
   Hierarchy Coverage Path Planning With Proactive Extremum Prevention in Unknown Environments

   2 citations · 2025

Key Collaborators

Contact & Links