As we start a new year, we wanted to take some time to share out best stories of 2022. Check out our top 5 blog posts and announcements from last year!
Clearpath Robotics Launches Outdoor Autonomy Software
In October 2022, we were excited to launch OutdoorNav, an autonomous navigation software platform designed for vehicle developers, OEMS, and robotics researchers. OutdoorNav, which is compatible with Clearpath’s outdoor mobile platforms as well as third party vehicles, provides robust and reliable point-to-point GPS-based autonomous navigation through proprietary fusion of vehicle sensor data. When paired with compatible hardware, the software also provides built-in obstacle detection and avoidance, as well as continuous path planning, allowing off-road vehicles to navigate autonomously between way-points collision-free. Read the full announcement here.
Research Team Advances Penguin Conservation Research With Robotics in Antarctica
What happens when you put penguins and robots together? One of the main drivers of the Woods Hole Oceanographic Institution‘s exciting project was global warming and its influence on the planet’s biodiversity, particularly how it impacts distinct animal groups. The researchers were seeking to reduce the human impact on biodiversity by monitoring emperor penguin colonies with the inconspicuous and unobtrusive eye of the Husky UGV based robot named ECHO. Learn more about how ECHO would be able to track individual penguins in Antarctica throughout their lifetimes, allowing researchers to gather data for behavioral and population dynamics research. Click here to read the full story.
Clearpath Robotics Launches TurtleBot 4
In May of 2022, we launched TurtleBot 4, the next generation of the world’s most popular open-source robotics platform. TurtleBot 4 is a low-cost, fully expandable mobile robotics platform with improved sensing, increased payload capacity, ROS 2 support and auto-docking capabilities for educators, researchers and developers.
TurtleBot 4 is shipped fully assembled with ROS 2 pre-installed and configured along with detailed user documentation, a Gazebo simulation model, and demo code, allowing users to get started right out-of-the-box! Read the full announcement here.
Saxion University of Applied Sciences Researches ROS 2 Fleet Management With Dingo
In February, 2022, we were happy to share a story about a project that was led by the Saxion University of Applied Sciences; one of the winning teams from our PartnerBot program in 2020. The team was awarded with a Dingo-D (differential drive) and we were excited to see how they would use their robot platform. Their goal was to facilitate the integration of mobile robots into automation ecosystems such as Enterprise Research Planning (ERP) and Manufacturing Execution and Control System (MES) through ROS 2 and Navigation 2 integration.
The team wanted to explore the possibilities of using ROS 2 in combination with fleet managers to control a fleet of different robots and eventually use it in various industrial applications. However, their main challenge prior to their PartnerBot win was creating an AGV that was industry-ready. Learn more about how the team was successfully able to install ROS 2 Foxy on Dingo-D, creating opportunities for Saxion’s partner companies to use open source AGVs for complex industrial tasks. Read the full article here.
Indiana University Explores Collision-Free Navigation in Cluttered Environments
Creating a safe, dependable, and robust control methodology for AGV autonomous navigation in unknown cluttered environments can be challenging. Such a navigation task requires the AGV to navigate safely and autonomously, to avoid getting trapped or colliding with static and dynamic obstacles while moving towards the goal.
Read our blog article on how the team at Vehicle Autonomy and Intelligence Lab (VAIL) at Indiana University used Jackal UGV to tackle these challenges while at the same time use a Sampling-based Model Predictive Control (MPC) method called log-MPPI. This algorithm was used for better exploration of state spaces. It also reduced the chance of the vehicle getting stuck in cluttered environments. Due to Jackal’s flexibility, the platform turned out to be the ideal tool for the lab. The MPPI algorithm was able to control the Jackal UGV directly via the ROS API with quick ROS sync functionality with an RVIZ GUI and a Gazebo model. To read the full article, click here.
These are just a few of our best stories and announcements from last year. We can’t wait to share more exciting stories with you in 2023. If you would like to read more interesting articles about Clearpath robots, news, and latest developments, you can visit our blog.