orb_slam_2_ros
A ROS implementation of ORB_SLAM2 (by appliedAI-Initiative)
sloam
Semantic LIDAR odometry and mapping for cylinderical objects (e.g. trees in forests) (by KumarRobotics)
| orb_slam_2_ros | sloam | |
|---|---|---|
| 1 | 1 | |
| 587 | 186 | |
| 2.7% | 3.8% | |
| 0.0 | 1.8 | |
| 9 months ago | over 1 year ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
orb_slam_2_ros
Posts with mentions or reviews of orb_slam_2_ros.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-02-28.
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Odometry is changing at a faster rate with intelrealsense d435 while using orb_slam2_ros
I have compiled [this repository](https://github.com/appliedAI-Initiative/orb_slam_2_ros) on nvidia jetson nano and it has been successfully built inside my catkin workspace. I have double checked the rosnode list and topics subscribed and published by nodes and they are all good. When I launched the file `roslaunch orb_slam2_ros orb_slam2_d435_rgbd.launch` and try to see the `/orb_slam2_rgbd/pose` topic, the pose looks quite unstable and changing at a faster rate (you can see inside the video attached) while the robot is static. I have attached the tf tree in this issue [frames.pdf](https://github.com/appliedAI-Initiative/orb_slam_2_ros/files/8130863/frames.pdf) and a video link [here](https://drive.google.com/file/d/1nU13ZrD_oXfTAPqC75yUB4uY-FzfR1dC/view?usp=sharing).
sloam
Posts with mentions or reviews of sloam.
We have used some of these posts to build our list of alternatives
and similar projects.
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Tree detection in forest using deep learning
You'd need to train on a lidar dataset, using point-cloud deep learning approaches. From experience and word-of-mouth, tree detection might be harder on single lidar scans (sweeps). But if you build a 3D map, then detection is easier. You can see that kind of work here : https://github.com/KumarRobotics/sloam
What are some alternatives?
When comparing orb_slam_2_ros and sloam you can also consider the following projects:
SuperPoint_SLAM - SuperPoint + ORB_SLAM2
hdl_graph_slam - 3D LIDAR-based Graph SLAM
Fast_RRT-ROS - RRT-ROS implementation.
salih_slam - Basic Visual Simultaneous Localisation & Mapping (VSLAM) implementation for three dimensional localisation.
Universal_Robots_ROS_Driver - Universal Robots ROS driver supporting CB3 and e-Series
Nox_robot - Nox robot project
ov2slam - OV²SLAM is a Fully Online and Versatile Visual SLAM for Real-Time Applications
stella_vslam - This is a unofficial fork of OpenVSLAM (https://github.com/xdspacelab/openvslam)
realsense-ros - ROS Wrapper for Intel(R) RealSense(TM) Cameras