110 citations · 361 across the 53 of their papers we have counts for
59 papers
Object-centric Representations for Interactive Online Learning with Non-Parametric Methods
Nikhil U. Shinde, Jacob Johnson, Sylvia Herbert +1
Large offline learning-based models have enabled robots to successfully interact with objects for a wide variety of tasks. However, these models rely on fairly consistent structure…
Investigating Low Data, Confidence Aware Image Prediction on Smooth Repetitive Videos using Gaussian Processes
Nikhil U. Shinde, Xiao Liang, Florian Richter +1
The ability to predict future states is crucial to informed decision-making while interacting with dynamic environments. With cameras providing a prevalent and information-rich sen…
Learning Sampling Dictionaries for Efficient and Generalizable Robot Motion Planning with Transformers
Jacob J Johnson, Ahmed H Qureshi, Michael Yip
Motion planning is integral to robotics applications such as autonomous driving, surgical robots, and industrial manipulators. Existing planning methods lack scalability to higher-…
SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation
Shan Lin, Yuheng Zhi, Michael C. Yip
Without ground truth supervision, self-supervised depth estimation can be trapped in a local minimum due to the gradient-locality issue of the photometric loss. In this paper, we p…
Markerless Camera-to-Robot Pose Estimation via Self-supervised Sim-to-Real Transfer
Jingpei Lu, Florian Richter, Michael C. Yip
Solving the camera-to-robot pose is a fundamental requirement for vision-based robot control, and is a process that takes considerable effort and cares to make accurate. Traditiona…
Image-based Pose Estimation and Shape Reconstruction for Robot Manipulators and Soft, Continuum Robots via Differentiable Rendering
Jingpei Lu, Fei Liu, Cedric Girerd +1
State estimation from measured data is crucial for robotic applications as autonomous systems rely on sensors to capture the motion and localize in the 3D world. Among sensors that…