We developed a miniaturized, vision-based suction cup that gives robotic manipulators a sense of touch — enabling autonomous alignment and the safe grasping of delicate, misaligned objects. Published in IEEE/ASME Transactions on Mechatronics (TMECH) and presented at AIM2026.

Key Contributions

  • Miniaturization: Shrank the system to a compact 22 × 40 mm footprint by integrating a micro-camera.
  • Simultaneous Multimodal Sensing: Real-time detection of 3-axis pressing forces and contact orientation for closed-loop surface alignment.
  • Universal Calibration: Our neural network applies universally to identically designed suction cups, eliminating the need for per-unit recalibration.
  • Enhanced Mechanical Performance: Achieved 36.3 kPa adhesion with just a 2.3 N preload to safely handle delicate, curved objects.

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