Our research focuses on automated and autonomous mobile machinery from task automation for operator assistance to high level of automation for autonomous operations.
Research
Research Focus
We develop algorithms for safe decision making in navigation and manipulation tasks of mobile machinery in outdoor working environments.
Mobile machinery are known by several terminologies: heavy-duty mobile machinery (HDMM), non-road mobile machinery (NRMM), mobile working machinery (MWM), off-highway machinery or equipment, etc. Regardless of the terminologies, our research focuses on the 3 most important characteristics of mobile machinery:
- They are mobile — navigation and/or driving from one location to another typically to transport material and load.
- They work — manipulation of physical materials to pick a load or transform the material.
- They operate in outdoor environments.
Thus, our research covers multiple domains: Robotics & Autonomous Systems; Machine Learning for Control; Sensor Fusion & Perception; Safety-Critical AI; Simulations.
Research Roadmap 2025-2030
Optimisation & Control
- Data-driven boom/crane motion
- Loss modeling
- Motion control & optimisation
Perception & Sensing
- Sensor calibration & state estimation
- MIMO Radar object detection
- SLAM (Simultaneous Localisation and Mapping)
Safe Motion Control
- Safety filters for real-world systems
- Safe control with map/perception input
Task Automation & Physical Interaction
- Loading & excavation
- Grappling (forestry & material handling)
- Terrain traversability
Simulation & Data-Driven Modeling
- World Modeling
- Sim-to-Real transfer
- Transfer learning
- Reinforcement Learning (RL)
Typical Applications
Construction
Mining
Forestry
Agriculture
Port & Yard Logistics
