Smart Auto-reforestation Robot Perception System for Complex Tropical Terrain

Smart Auto-reforestation Robot Perception System for Complex Tropical Terrain

Advisor/s

Dr. Tao (Kevin) Huang

College or Research Centre

College of Science & Engineering

Summary of Project

Planting trees in tropical regions is essential for mitigating climate change, preserving biodiversity, regulating water systems, protecting soil, and providing economic benefits. However, the complex terrain in tropical areas, characterised by an uneven surface, slippery nature, dense vegetation, and deep slopes, poses significant challenges for conventional tree-planting robots.

This project aims to develop a next-generation robot perception system for auto-reforestation robots. The project will leverage cutting-edge artificial intelligence and sensor technologies, considering the robustness, adaptability, and flexibility required for tropical terrain. The developed perception system will enable the auto-reforestation Robot to understand the surrounding environment, helping it navigate challenging terrain, accurately identify suitable planting locations, and efficiently plant trees.

Expected outcomes of this project include multi-modal deep learning algorithms with enhanced perception capabilities for tropical reforestation robots, which will enable more effective and sustainable reforestation efforts. This project has significant environmental, economic, and social benefits by contributing to global climate change mitigation efforts, protecting biodiversity, and supporting local economies. The project's impact lies in its potential to revolutionise reforestation efforts, create a scalable, cost-effective, and sustainable solution to the challenges of tropical terrain, and inform future developments in smart robots for environmental applications.

Key Words

Perception systems; robots; complex tropical terrain; AI; sensor technology

Would suit an applicant who

This project suits a candidate with a Bachelor's or Master's degree in Robotics, Artificial Intelligence, Computer Science, Electrical Engineering, or a related field. They should have strong technical skills in robotics, artificial intelligence, and computer vision and proficiency in programming languages like Python, C++, and ROS. Excellent communication and interpersonal skills are necessary for collaborating with other researchers, stakeholders, and industry partners.

Desirable skills and qualifications for the candidate include familiarity with transformers, multi-modal data fusion, and reinforcement learning. Experience with sensor technologies such as LIDAR, Radar, cameras, and data processing methods for sensor data would be beneficial. Prior publication and fieldwork experiences are also desirable.

Updated: 14 Jul 2023