50 citations · 53 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
Real-time LIDAR localization in natural and urban environments
Georgi Tinchev, Adrian Penate-Sanchez, Maurice Fallon
Localization is a key challenge in many robotics applications. In this work we explore LIDAR-based global localization in both urban and natural environments and develop a method s…
Online LiDAR-SLAM for Legged Robots with Robust Registration and Deep-Learned Loop Closure
Milad Ramezani, Georgi Tinchev, Egor Iuganov +1
In this paper, we present a factor-graph LiDAR-SLAM system which incorporates a state-of-the-art deeply learned feature-based loop closure detector to enable a legged robot to loca…
Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU
Georgi Tinchev, Adrian Penate-Sanchez, Maurice Fallon
Localization in challenging, natural environments such as forests or woodlands is an important capability for many applications from guiding a robot navigating along a forest trail…
Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments
Georgi Tinchev, Simona Nobili, Maurice Fallon
In this work we introduce Natural Segmentation and Matching (NSM), an algorithm for reliable localization, using laser, in both urban and natural environments. Current state-of-the…