The AgileX Robotics Promotes an Upgraded Quality of Scientific Research and Education with ROS2
The birth of ROS has allowed the robotic industry to develop rapidly under a common framework. Based on the creation of a diverse robotic ecosystem and the application of ROS, the robotic control, perception and decision-making can be better organized and operated. With the gradual deepening of robot research, design, and application, robots have been deployed in a variety of environments, such as logistics and distribution, security and inspection, special operations, etc. As a result of diverse industry applications, there are also increasingly high demands for robot navigation, tasks, scheduling, operation, system stability and scalability, and even cost assessment.
When the ROS 1 version faces these demands, problems, such as its single robot system, single platform, poor real-time performance, poor stability, high network requirements and poor confidentiality, have also gradually emerged, and it is gradually failing to meet the task requirements that complex environments demand from robots currently. The birth and application of the ROS 2 provides the possibility and feasibility for robots to break through current bottleneck in development. Based on this, the AgileX Robotics Research and Education Team carefully sorted out the current industry needs and concerns through in-depth exploration and research on the ROS 2 version, designed and developed the world’s first ROS 2 mobile robot open source navigation education kit - ROS 2 EDU Kit.
The ROS 2 EDU Kit is available in 2 versions — ROS 2 EDU Lite and ROS 2 EDU Pro — to meet the research, education, and usage needs of different users. The kit is based on the AgileX autonomous mobile robot platform - SCOUT MINI series, with the ROS 2 Foxy version as the core, equipped with 2D LiDAR, 9-axis IMU, a dual purpose depth camera, and other sensors. The industrial control machine adopts the X86 architecture and provides new features, including NAV 2 and Gazebo 11, which is based on the Ubuntu 20.04 system. The NAV 2 core navigation components are fully compatible with the official new features of NAV, providing a comprehensive and in-depth ROS 2 learning and research integrated robot development platform for scientific education.
What the ROS 2 NAV Kit does.
1) The ROS 2 NAV Kit has a full version of the ROS 2 Foxy, so you can experience the new features of ROS 2 in its entirety.
Figure 1: ROS2 FOXY FITZROY
2) The ROS 2 ROS Kit is installed with Gazebo 11 simulation development environment. You can simulate it in the visual interface, or you can get the ROS 2 simulation package on the official Github platform for AgileX Robotics (all models support ROS 2), which is more efficient and convenient.
Figure 2: Based on Gazebo 11 path simulation
3) The ROS 2 EDU Kit can build a point cloud map based on Cartographer.
Figure 3: Built on Cartographer’s point cloud map
4) The ROS 2 EDU Kit can conduct SLAM algorithm research and demonstration based on NAV 2 Navigation Stack.
Figure 4: Construction of indoor environment SLAM algorithm
Figure 5: NAV2 navigation stack
5) ROS 2 EDU Kit supports NAV 2 navigation stack
Figure 6: Robot barrier avoidance algorithm
Figure 7: Robotic indoor environment barrier avoidance algorithm simulation
6) ROS 2 EDU Kit also supports NOMACTHING remote programming
To make it easier for everyone to see the difference between ROS 2 and ROS 1, we will list the corresponding new features as follows:
The AgileX Robotics NAV Kit adapts all features of ROS2 and supports the user to conduct mobile robot research and development based on ROS2. In recent years, the research has peaked the interests of those concerned with agricultural applications, military applications, outdoor measurement and exploration, patrol and security, and other industrial applications, as well as unmanned vehicle research. It has software and hardware functions for scientific research, teaching, and presentations, and it can be developed, tested, and distributed safely and cost-effectively.
As a leader in the ROS open source ecosystem, AgileX Robotics has a strong understanding of the needs and difficulties of ROS2 scenarios, and, from the customer’s perspective, AgileX’s full series of chassis also supports ROS2 simultaneously. AgileX aims to reduce the ROS2 development threshold, improve the high modularity and multiplexing capabilities of robots, simplify the task volume, and experience the efficiency of human and machine intelligence collaboration.
The detailed information of ROS2 kit can be obtained from the AgileX official Github or from marketing and sales personnel. Everyone is also welcomed to post their experiences and feedback on the official AgileX online community (https://community.agilex.ai). We will also publish technical articles regularly, and everyone can chat on the AgileX community and Github.
