학술논문

Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment
Document Type
Conference
Source
2021 20th International Conference on Advanced Robotics (ICAR) Advanced Robotics (ICAR), 2021 20th International Conference on. :857-864 Dec, 2021
Subject
Robotics and Control Systems
Location awareness
Service robots
Software algorithms
Wheels
Benchmark testing
Sensor fusion
Robot sensing systems
Language
Abstract
To arrive at a realistic assessment of localization methods in terms of their performance in an industrial environment under various challenging conditions, we provide a benchmark to evaluate algorithms both for individual components as well as multi-sensor systems. For several sensor types, including wheel odometry, RGB cameras, RGB-D cameras, and LIDAR, potential issues were identified. The accuracy of wheel odometry, for example, when there are bumps on the track. For each sensor type, we explicitly chose a track for the benchmark dataset containing situations where the sensor fails to provide adequate measurements. Based on the acquired sensor data, localization can be achieved either using a single sensor information or sensor fusion. To help evaluate the output of associated localization algorithms, we provide a software to evaluate a set of metrics as part of the paper. An example application of the benchmark with state-of-the-art algorithms for each sensor is also provided.