We’re thrilled to showcase our #autonomy and #AI at EarthSense! Thanks to the amazing work from our team, our TerraMax robot is making an impact in oil palm through full-field autonomy. If you would like to be part of the future of #AgriculturalRobotics, reach out to us to start a conversation! #AgTech #Robotics #Sustainability #OilPalm
Here's how ground autonomy in agriculture works. For context, I'm sharing a video of our TerraMax robot navigating autonomously in oil palm. We are visualizing neural network detections, lane detection, and the robot's map of its surroundings. Deploying autonomous agricultural robots is hard. It requires dealing with rough terrain and a lack of existing datasets. But there's a simple framework we follow at EarthSense, Inc. to break it down. Solving autonomy in row crops like corn & oil palm requires stacking together the following solutions. 1. 🛣️ Straight Line Navigation Whether you're monitoring plants, spraying pesticides, or spreading fertilizer, you need to traverse the rows. Your perception needs to find the middle to drive towards, and the danger zones to avoid on each side. Your high level controller needs to find a path towards the middle. 2. ↪️ Lane Turning Straight Line gets you the row. Lane Turning completes the field. Your perception needs to find where the current row ends, where the next row starts, and build a map of the turn. Then you need to find the optimal path forward, balancing traversability, safety, and speed concerns. 3. 🚶➡️ Obstacle Detection & Avoidance You need to keep both the robot and field workers safe. Your perception needs to find objects and regions of interest in your environment, and avoid them. If they get too close, the robot must stop entirely. 🏁 Once you stack up these solutions, you have an autonomous robot. Autonomy is never easy. But a good framework makes it possible. Follow for more deep dives into agricultural robotics and field autonomy. #AI #AgricultureRobots #Robots #Autonomy