Luis Felipe Casas — accepted AI-conference papers

2025

RobotFingerPrint: Unified Gripper Coordinate Space for Multi-Gripper Grasp Synthesis and Transfer

Ninad Khargonkar, Luis Felipe Casas, Balakrishnan Prabhakaran, Yu Xiang

IROS 2025

We introduce a novel grasp representation named the Unified Gripper Coordinate Space (UGCS) for grasp synthesis and grasp transfer. Our representation leverages spherical coordinates to create a shared coordinate space across different robot grippers, enabling it to synthesize and transfer grasps fo

Cited by 1 Source ↗Scholar ↗

2024

MultiGripperGrasp: A Dataset for Robotic Grasping from Parallel Jaw Grippers to Dexterous Hands

Luis Felipe Casas, Ninad Khargonkar, Balakrishnan Prabhakaran, Yu Xiang

IROS 2024poster

We introduce a large-scale dataset named MultiGripperGrasp for robotic grasping. Our dataset contains 30.4M grasps from 11 grippers for 345 objects. These grippers range from two-finger grippers to five-finger grippers, including a human hand. All grasps in the dataset are verified in the robot simu…

Cited by 8 Source ↗Scholar ↗