Research Projects

Resilience is crucial for a system to overcome unexpected failures, especially during the pandemic. Robotic systems struggle with uncertainties, especially in assembly applications where positioning accuracy is less than clearance. This leads to high chances of failure or increased process time. Industries often avoid using robotic assembly systems in manufacturing lines. However, resilience can be mitigated using multiple modalities of controlling the robot. This work proposes automated assembly using vision and fusion of force/torque and vision data. A human-in-the-loop system will also be studied to mitigate failures, resulting in a resilient system capable of performing assembly using multiple modalities. This approach could help industries overcome the challenges of the pandemic and improve their manufacturing processes.