Curating Long-term Vector Maps

07/30/2020
by   Samer Nashed, et al.
0

Autonomous service mobile robots need to consistently, accurately, and robustly localize in human environments despite changes to such environments over time. Episodic non-Markov Localization addresses the challenge of localization in such changing environments by classifying observations as arising from Long-Term, Short-Term, or Dynamic Features. However, in order to do so, EnML relies on an estimate of the Long-Term Vector Map (LTVM) that does not change over time. In this paper, we introduce a recursive algorithm to build and update the LTVM over time by reasoning about visibility constraints of objects observed over multiple robot deployments. We use a signed distance function (SDF) to filter out observations of short-term and dynamic features from multiple deployments of the robot. The remaining long-term observations are used to build a vector map by robust local linear regression. The uncertainty in the resulting LTVM is computed via Monte Carlo resampling the observations arising from long-term features. By combining occupancy-grid based SDF filtering of observations with continuous space regression of the filtered observations, our proposed approach builds, updates, and amends LTVMs over time, reasoning about all observations from all robot deployments in an environment. We present experimental results demonstrating the accuracy, robustness, and compact nature of the extracted LTVMs from several long-term robot datasets.

READ FULL TEXT

page 1

page 2

page 3

page 4

page 5

page 6

research
10/04/2022

Long-Term Localization using Semantic Cues in Floor Plan Maps

Lifelong localization in a given map is an essential capability for auto...
research
09/30/2021

Probabilistic Object Maps for Long-Term Robot Localization

Robots deployed in settings such as warehouses and parking lots must cop...
research
07/02/2018

Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data

This paper presents a novel semantic mapping approach, Recurrent-OctoMap...
research
12/30/2022

Long-Term Online Multi-Session Graph-Based SPLAM with Memory Management

For long-term simultaneous planning, localization and mapping (SPLAM), a...
research
10/16/2009

An Idiotypic Immune Network as a Short Term Learning Architecture for Mobile Robots

A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approa...
research
09/26/2018

Identifying robust landmarks in feature-based maps

To operate in an urban environment, an automated vehicle must be capable...
research
06/15/2010

Two-Timescale Learning Using Idiotypic Behaviour Mediation For A Navigating Mobile Robot

A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approa...

Please sign up or login with your details

Forgot password? Click here to reset