Priyansh Sinha supervised by Dr. Nagamanikandan Govindan received his Master of Science in Computer Science and Engineering (CSE). Here’s a summary of his research work on Planning and Control Strategies for Contact-Rich,Non-Prehensile Mobile Manipulation:
With the advent of Industry 4.0, the demands on industrial robots have expanded beyond simple pick-and-place tasks. Future smart factories require robots capable of a wide range of manipulation skills, including the ability to manipulate objects with variety of actions like pushing. This thesis investigates the capabilities of a manipulator and the system to perform fine or controlled non-prehensile manipulation (without grasping the objects), potentially exceeding the robot arm’s reachable workspace.
Key contributions of this research include:
- Hybrid Planner combining Striking, Pushing and Pick and Place motions.
- Development of sophisticated optimal control strategies for generating manipulation of objects to specific target locations with high precision without necessarily grasping. These algorithms calculate the optimal contact point,force and velocity required for each action.
- Conducting experiments primarily in a simulation environment to validate the effectiveness of the end-effector design and its control algorithms, complemented by preliminary tests on a real robot. These evaluations demonstrate the practical viability and robustness of the proposed system under controlled conditions.
The thesis further explores the vast practical implications of Non-Prehensile manipulation. In warehouse logistics, this technology can significantly optimize sorting, material transfer, and distribution processes by enabling faster and more precise handling of items. By combining optimization and planning strategies, this research provides a comprehensive framework for designing a framework for hybrid manipulation. This interdisciplinary methodology enhances the versatility, adaptability, and performance of robots, ultimately improving efficiency, safety, and productivity in various industrial and operational settings.
July 2025