Work

A Benchmark Dataset for Collaborative SLAM in Service Environments

Year: 2024

Type: article

Abstract: We introduce a new multi-modal collaborative SLAM (C-SLAM) dataset for multiple service robots in various indoor service environments, calledC-SLAM dataset inServiceEnvironments (CSE). We use the NVIDIA Isaac Sim to generate data in various indoor service environments with the challenges that may occur in real-world service environments. By using the simulator, we can provide precisely time-synchronized sensor data, such as stereo RGB/depth, IMU, and ground truth (GT) poses. We configure three common indoor service environments (Hospital,Office, andWarehouse), each featuring dynamic objects performing motions suited to the environment. In addition, we drive the robots to mimic the actions of real service robots. Through these factors, we generate a realistic C-SLAM dataset for multiple service robots. We demonstrate ourCSEdataset by evaluating diverse state-of-the-art single-robot SLAM and multi-robot SLAM methods. Additionally, we provide a detailed tutorial on generating C-SLAM data using the simulator.

Source: IEEE Robotics and Automation Letters

DOI: 10.1109/lra.2024.3491415

Authors: Harin Park, Inha Lee, Minje Kim, Hyungyu Park, Kyungdon Joo

Institution: Ulsan National Institute of Science and Technology

Language: English

Topic: Robotics and Sensor-Based Localization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green