| Proj No. | A3216-251 |
| Title | Learning World Models for Autonomous Robots |
| Summary | This project explores how robots can learn compact, predictive models of their environment — known as world models — to enable planning, reasoning, and decision-making. It involves the exploration of world model architectures, training a world model using simulation or real-world data, and integrating it with a control policy to perform robotics tasks. |
| Supervisor | Ast/P Wang Ziwei (Loc:S2 > S2 B2C > S2 B2C 83, Ext: +65 67906366) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Centre for Advanced Robotics Technology Innovation (CARTIN) (Loc: S2.1-B3-01) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |