Plant detection and mapping for agricultural robots using a 3D LIDAR sensor

By Ulrich Weiss, Peter Biber. Robotics Auton. Syst., 2011

295 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/954d01c5c85cf4b60de91165fccf407a86db1b37

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Jochen Hemming
2. Yael Edan
3. Girish V. Chowdhary
4. Eldert J. van Henten
5. Cornelis Wouter Bac

In Environmental Engineering

1. Jochen Hemming
2. Yael Edan
3. Eldert J. van Henten
4. Cornelis Wouter Bac

In Plant Science

1. Jochen Hemming
2. Yael Edan
3. Eldert J. van Henten
4. Cornelis Wouter Bac
5. Tony E. Grift
6. Siva K. Balasundram

Citations in the corpus

• Harvesting Robots for High‐value Crops: State‐of‐the‐art Review and Challenges Ahead (2014, methodology): “To plan appropriate actions, sensor data from multiple sensor types can be fused into a world model containing 3D crop models (Weiss & Biber, 2011) and other objects and behavior in the environment.”
• Research and development in agricultural robotics: a perspective of digital farming. (2018, methodology): “…systems for development of field robots that can be used in yield estimation [42,58,59] , thinning [60] , weeding and targeted spraying [61-64] , seedling and transplanting [65,66] , delicate handling of sensitive flowers [67,68] , and multipurpose autonomous field navigation robots [18,69-75] .”