Aris Munandar
Papers
1
Total Citations
3
H-Index
1
About
Aris Munandar is a robotics researcher advancing the accessibility and safety of robotic grasping through open-source hardware design and soft sensing technologies. His work centers on developing low-cost, parallel grippers that integrate embedded soft skin fingertip sensors, enabling safer and more effective physical interaction between robots and their environments. By addressing the prohibitive costs of commercial grippers, Munandar’s designs empower laboratories and educational institutions with limited budgets to conduct experimental studies in manipulation and grasping. His most-cited paper, "An open-source parallel gripper with an embedded soft skin fingertip sensor" (2023), has garnered 3 citations, reflecting its emerging impact in the field. This work exemplifies his commitment to democratizing robotics research—combining mechanical simplicity with sensorized soft materials to improve grip stability and tactile feedback. Munandar’s contributions are particularly relevant as the demand for robots in daily life grows, where safe, adaptive grasping is critical. His open-source approach not only accelerates innovation but also fosters reproducibility and collaboration, positioning him as a key figure in making robotic manipulation more accessible and practical for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1