4 papers
InstaLoc: One-shot Global Lidar Localisation in Indoor Environments through Instance Learning
Lintong Zhang, Tejaswi Digumarti, Georgi Tinchev +1
Localization for autonomous robots in prior maps is crucial for their functionality. This paper offers a solution to this problem for indoor environments called InstaLoc, which ope…
3D Lidar Reconstruction with Probabilistic Depth Completion for Robotic Navigation
Yifu Tao, Marija Popović, Yiduo Wang +3
Safe motion planning in robotics requires planning into space which has been verified to be free of obstacles. However, obtaining such environment representations using lidars is c…
Fast-Learning Grasping and Pre-Grasping via Clutter Quantization and Q-map Masking
Dafa Ren, Xiaoqiang Ren, Xiaofan Wang +2
Grasping objects in cluttered scenarios is a challenging task in robotics. Performing pre-grasp actions such as pushing and shifting to scatter objects is a way to reduce clutter.…
Unsupervised Learning of Depth Estimation and Visual Odometry for Sparse Light Field Cameras
S. Tejaswi Digumarti, Joseph Daniel, Ahalya Ravendran +1
While an exciting diversity of new imaging devices is emerging that could dramatically improve robotic perception, the challenges of calibrating and interpreting these cameras have…