Andrew W. Palmer — accepted AI-conference papers

2019

Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles

Florian Tschopp, Thomas Schneider, Andrew W. Palmer, Navid Nourani-Vatani, Cesar Cadena, Roland Siegwart +1

RA-L 2019

Today, rail vehicle localization is based on infrastructure-side Balises (beacons) together with on-board odometry to determine whether a rail segment is occupied. Such a coarse locking leads to a sub-optimal usage of the rail networks. New railway standards propose the use of moving blocks centred

Cited by 41 Source ↗Scholar ↗

2018

Modelling Resource Contention in Multi-Robot Task Allocation Problems with Uncertain Timing

Andrew W. Palmer, Andrew J. Hill, Steven J. Scheding

ICRA 2018poster

This paper proposes an analytical framework for modelling resource contention in multi-robot systems, where the travel times and task durations are uncertain. It uses several approximation methods to quickly and accurately calculate the probability distributions describing the times at which the tas…

Cited by 24 Source ↗Scholar ↗

2018

Robust Odometry using Sensor Consensus Analysis

Andrew W. Palmer, Navid Nourani-Vatani

IROS 2018poster

Odometry forms an important component of many manned and autonomous systems. In the rail industry in particular, having precise and robust odometry is crucial for the correct operation of the Automatic Train Protection systems that ensure the safety of high-speed trains in operation around the world…

Cited by 9 Source ↗Scholar ↗