Lidar technology is becoming more prevalent in autonomous systems and robots. This technology enables 3D perception of the environment and accurate object detection. This is valuable for machines that need to navigate, recognize obstacles, or map their surroundings. Looking beyond the agricultural market reveals new ways in which sensor technology, such as lidar, can add value to agricultural machinery.
With lidar, agricultural machinery can navigate more safely, avoid obstacles, and better understand its surroundings, even in situations involving mud, vibrations, and varying light conditions. Learning from applications in other sectors yields new ideas for practical lidar applications in agriculture. We use robust lidars from Ouster that perform well in harsh conditions.
Challenges in the agricultural market
Integrating sensors into agricultural machinery presents several typical challenges.
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Dust and dirt
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Severe vibrations caused by moving machinery
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Weather conditions, such as rain, sun, and temperature fluctuations
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Complex and irregular objects such as crops, bales, and animals
- Dynamic environments with people, animals, and other machines on the farm
Sensors must be accurate, robust, and reliable in harsh conditions. These are precisely the conditions that many autonomous systems in other sectors also face.
3 real-world examples of lidar applications
Example 1: autonomous robots
Trombia develops autonomous electric street sweepers that clean streets on their own. These machines use lidar sensors for navigation and obstacle detection.
The challenges of an autonomous sweeper overlap with autonomous applications in the agricultural sector. For example, the machine must continue to function reliably in an environment with high levels of dust and debris in the air, changing weather conditions, and complex objects such as curbs, vehicles, and pedestrians.
This application uses Ouster digital lidar to continuously generate a 3D image of its surroundings. This allows the machine to detect obstacles and navigate safely.
Because lidar is an active sensor with its own light source, it operates effectively in the dark without additional lighting. In conditions with dust or changing light - where cameras struggle - lidar continues to perform reliably.
In autonomous agricultural applications, for example, a machine must be able to recognize obstacles, navigate around them safely, and continue functioning reliably in dusty and dirty environments. In agriculture, this translates to applications such as the following:
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A feed-pushing robot in a barn that drives autonomously along fences and feeding stations
- A field robot that navigates autonomously between rows of crops
Example 2: autonomous off-road vehicles
Forterra develops technology that enables defense vehicles to drive autonomously in challenging off-road environments. These include terrain without lanes, with limited visibility, bad weather, and limited GPS coverage. Their systems ensure that vehicles continue to operate safely, stably, and reliably under these harsh conditions.
Lidar is one of the most important sensors in Forterra’s solutions. It provides a continuous and accurate 3D image of the environment, all around the vehicle. The digital lidar sensors precisely measure distances and obstacles. This allows these autonomous vehicles to drive safely, without lanes or fixed reference points.
Lidar continues to function effectively in environments where visibility and GPS are less reliable. This enables vehicles to safely navigate complex and unpredictable situations.
Similar challenges arise in agriculture, including off-road navigation, changing weather conditions, and pollution. Autonomous solutions help address labor shortages.
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Self-driving tractors
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Unmanned field robots
- Other vehicles that operate independently in fields and pastures
Example 3: mapping with drones
Deep Forestry develops autonomous inspection drones that use lidar to scan and map complex environments.
This drone uses an Ouster lidar system to build a 3D map of the forest. It determines the distance to every tree and surface, generating a detailed point cloud of the terrain and vegetation.
Similar to its use in forestry, lidar can be used in agriculture to create an accurate 3D image of the terrain and crops. This enables analyses and smart applications, such as precision agriculture. Examples of agricultural applications include:
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3D mapping of fields for overviews and planning
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Volume measurements of crops or harvested products
- Analysis of terrain structure and vegetation for better crop insights
A point cloud image generated by a lidar sensor. The environment appears as thousands of data points that together form a 3D view. This is what lidar “sees”: an accurate 3D representation based on distance and reflection. Objects such as walls, vehicles, and obstacles are visible as clear shapes in the point cloud.
Key considerations for lidar integration
For original equipment manufacturers (OEMs) looking to integrate LiDAR into agricultural machinery, more is required than simply mounting the sensor. Although lidar systems offer advantages, their success depends heavily on how they are integrated and how the data is processed. Some key considerations are:
- Mounting position
The position of the sensor determines the field of view and potential blind spots. Lidar sensors are often mounted higher on the machine to provide a better overview of the surroundings.
- Protection against dirt
Mud, and water can affect the optics. Depending on the application, a protective cover, airflow, or cleaning mechanism may be necessary.
- Vibrations
Agricultural machinery often produces strong vibrations. Stable mounting and vibration damping help maintain measurement accuracy.
- Data processing
Lidar generates large amounts of data. For real-time applications such as navigation, the appropriate software must process this data quickly.
Practical lidar integration with Ouster and Sentech
For the integration of digital lidar sensors, we work together with our partner Ouster. Their sensors are a key element throughout the practical use cases in this blog.
Together, we bring the technology into real-world applications: Ouster provides the hardware, and Sentech offers local support and integration expertise in the Netherlands. This helps machine builders bridge the gap between sensor and a working solution.
