5 citations · 5 across the 8 of their papers we have counts for
8 papers
HRT1: One-Shot Human-to-Robot Trajectory Transfer for Mobile Manipulation
Sai Haneesh Allu, Jishnu Jaykumar P, Ninad Khargonkar +3
We introduce a novel system for human-to-robot trajectory transfer that enables robots to manipulate objects by learning from human demonstration videos. The system consists of fou…
RobotFingerPrint: Unified Gripper Coordinate Space for Multi-Gripper Grasp Synthesis and Transfer
Ninad Khargonkar, Luis Felipe Casas, Balakrishnan Prabhakaran +1
We introduce a novel grasp representation named the Unified Gripper Coordinate Space (UGCS) for grasp synthesis and grasp transfer. Our representation leverages spherical coordinat…
RISeg: Robot Interactive Object Segmentation via Body Frame-Invariant Features
Howard H. Qian, Yangxiao Lu, Kejia Ren +4
In order to successfully perform manipulation tasks in new environments, such as grasping, robots must be proficient in segmenting unseen objects from the background and/or other o…
MultiGripperGrasp: A Dataset for Robotic Grasping from Parallel Jaw Grippers to Dexterous Hands
Luis Felipe Casas, Ninad Khargonkar, Balakrishnan Prabhakaran +1
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-f…
SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenes
Ninad Khargonkar, Sai Haneesh Allu, Yangxiao Lu +3
We present a new reproducible benchmark for evaluating robot manipulation in the real world, specifically focusing on pick-and-place. Our benchmark uses the YCB objects, a commonly…
Skeletal Point Representations with Geometric Deep Learning
Ninad Khargonkar, Beatriz Paniagua, Jared Vicory
Skeletonization has been a popular shape analysis technique that models both the interior and exterior of an object. Existing template-based calculations of skeletal models from an…
Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction
Yangxiao Lu, Ninad Khargonkar, Zesheng Xu +6
We introduce a novel robotic system for improving unseen object instance segmentation in the real world by leveraging long-term robot interaction with objects. Previous approaches…
NeuralGrasps: Learning Implicit Representations for Grasps of Multiple Robotic Hands
Ninad Khargonkar, Neil Song, Zesheng Xu +2
We introduce a neural implicit representation for grasps of objects from multiple robotic hands. Different grasps across multiple robotic hands are encoded into a shared latent spa…