Dongdong Du

About

Dongdong Du is a robotics and agricultural automation researcher whose work bridges soft robotics, autonomous navigation, and precision agriculture. His most impactful contributions center on developing intelligent harvesting systems, exemplified by his 2024 study on a selective harvesting robot for broccoli, which integrates perception, manipulation, and field deployment. This work, along with his 2025 paper on maturity recognition and localization of broccoli under occlusion using RGB-D instance segmentation, demonstrates his focus on overcoming real-world challenges in agricultural robotics—such as occlusion and variable crop conditions. Du has also advanced soft robotics through a 2024 study that uses transfer learning from FEM data to model soft fiber-reinforced bending actuators, offering efficient design tools for compliant grippers. In mobile robotics, his 2020 paper on an improved RRT algorithm for path planning, which enhances the basic RRT with ant colony optimization for shorter, more efficient paths, has garnered attention in the field. With over 46 citations across his most-cited works, Du’s research is characterized by its practical integration of machine learning, computer vision, and robotic control, aiming to automate labor-intensive tasks in agriculture and enable more adaptable robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Design, integration, and field evaluation of a selective harvesting robot for broccoli

   15 citations · 2024
2. 2
   Modelling of soft fiber-reinforced bending actuators through transfer learning from a machine learning algorithm trained from FEM data

   15 citations · 2024
3. 3
   Maturity recognition and localisation of broccoli under occlusion based on RGB-D instance segmentation network

   8 citations · 2025
4. 4
   Path Planning for Mobile Robots Based on Improved RRT Algorithm

   8 citations · 2020

Key Collaborators

Contact & Links