Experiment results for the paper titled “Comprehensive analysis of optimization-based obstacle avoidance for agricultural robotics in the greenhouse environment”

Citation Author(s):
Mustofa
Basri
Khalifa University
Submitted by:
Mustofa Basri
Last updated:
Thu, 12/19/2024 - 02:23
DOI:
10.21227/vsc8-cx57
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Abstract 

This dataset contains simulated and real-world experimental data associated with the paper “Comprehensive Analysis of Optimization-Based Obstacle Avoidance for Agricultural Robotics in Greenhouse Environments.” The dataset from the simulated environment comprises multiple CSV files generated from the Gazebo simulation of a differential robot, the Stretch Robot. These files document the robot's movement, capturing data from the Gazebo model topic. Each CSV file includes timestamps, coordinates along the x, y, and z axes, and the robot’s heading angle (yaw), all based on Gazebo’s coordinate system.

The data collected from real-world experiments was recorded by subscribing to the robot's odometry topics, creating a real-time dataset reflecting its actual movement and odometry calculations. These datasets provide valuable insights for analyzing optimization-based obstacle avoidance in simulated and real-world greenhouse settings.

 

Instructions: 

The dataset from the gazebo simulated environment starts with the filename “simulated_,” and the dataset from the real-world experiment starts with the filename “real_.”

The simulated dataset's structure is as follows:

  • timestamps
  • coordinates along the x, y, and z axes, and the robot’s heading angle (yaw), all based on Gazebo’s coordinate system.

As for example, if we want to access the data from the simulated experiment, from the A* global planner and DWA local planner, we can search the filaname "Simulated_DWA-Astar".   

Similarly, the real-world experiment datasets structure contains time, coordinates along the x, y, and z axes, and the robot’s heading angle (yaw), all based on the odometry coordinate system of the robot, which its initial position is based on the first position when the robot is turned on.

Funding Agency: 
Khalifa University
Grant Number: 
RC1-2018-KUCARS