Integrated Industrial & Vision-Guided Robotics (Course Project)
Overview
Developed an integrated robotics system combining collaborative manipulators and autonomous mobile robots (AMRs) to execute coordinated pick-and-place and material-handling tasks in both simulation and real hardware.
Key Components
Industrial Robotics Integration
- Programmed and integrated two collaborative manipulators and AMRs to execute coordinated pick-and-place and material-handling tasks
- Formed a fully automated workflow with seamless robot coordination
Vision-Guided Manipulation Pipeline
- Developed in both simulation (Isaac Sim / CoppeliaSim) and real hardware
- Object detection and localization using computer vision
- Motion planning for grasping with collision avoidance
- Inverse kinematics-based target reaching with visual servoing for object tracking
Multimodal Imitation Learning
- Extended the system to a multimodal imitation learning framework for bimanual robotic manipulation
- Trained policies in IsaacSim and deployed them on real robots
- Improved manipulation precision and generalization across diverse tasks and platforms
Tools & Technologies
Simulation: IsaacSim, CoppeliaSim
Control Systems: TMflow, Fetchcore
Frameworks: ROS, Imitation Learning