activity
20162023
most citedCore Challenges of Social Robot Navigation: A Survey

34 citations · 197 across the 45 of their papers we have counts for

collaborators

46 papers

cs.RO2023

SoRTS: Learned Tree Search for Long Horizon Social Robot Navigation

Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4

The fast-growing demand for fully autonomous robots in shared spaces calls for the development of trustworthy agents that can safely and seamlessly navigate in crowded environments…

cs.CV2023

EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting

Inhwan Bae, Jean Oh, Hae-Gon Jeon

Capturing high-dimensional social interactions and feasible futures is essential for predicting trajectories. To address this complex nature, several attempts have been devoted to…

cs.RO2023★ 1 cited

Designing Anthropomorphic Soft Hands through Interaction

Pragna Mannam, Kenneth Shaw, Dominik Bauer +3

Modeling and simulating soft robot hands can aid in design iteration for complex and high degree-of-freedom (DoF) morphologies. This can be further supplemented by iterating on the…

cs.CV2023

FishRecGAN: An End to End GAN Based Network for Fisheye Rectification and Calibration

Xin Shen, Kyungdon Joo, Jean Oh

We propose an end-to-end deep learning approach to rectify fisheye images and simultaneously calibrate camera intrinsic and distortion parameters. Our method consists of two parts:…

cs.CV2023★ 1 cited

Regularizing Self-training for Unsupervised Domain Adaptation via Structural Constraints

Rajshekhar Das, Jonathan Francis, Sanket Vaibhav Mehta +3

Self-training based on pseudo-labels has emerged as a dominant approach for addressing conditional distribution shifts in unsupervised domain adaptation (UDA) for semantic segmenta…

cs.RO2023

Core Challenges in Embodied Vision-Language Planning

Jonathan Francis, Nariaki Kitamura, Felix Labelle +3

Recent advances in the areas of Multimodal Machine Learning and Artificial Intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision…