Perception and manipulation systems for forest automation
[Open soon]
Work description
As part of the SMARTCUT.v2 project, INESC TEC aims to develop automation solutions for operations in forest environments, including vegetation detection and handling. The work will focus on developing robust perception systems capable of operating in complex and variable natural environments, combining data from multiple sensors (3D LiDAR, RGB-D cameras, and monocular vision) with deep learning techniques. The handling component will also be explored, including motion planning and actuator control for tasks such as selective vegetation thinning and harvesting of non-timber organic matter. The activities will be developed in a laboratory environment and in real forest scenarios, in collaboration with partner entities from the forestry sector and the project consortium.
Academic Qualifications
Master's degree in Electrical Engineering with a focus on Robotics and Automation.
Minimum profile required
Master's degree in Electrical Engineering with a focus on Robotics and Automation.Enrollment in a doctoral program.
Preference factors
Experience in robotic perception systems, computer vision, and sensor fusion. Knowledge of deep learning applied to segmentation/detection in natural environments. Experience in robotic manipulation in unstructured environments. Previous experience in forestry or agricultural robotics. Knowledge of ROS/ROS2 and sensor integration (LiDAR, RGB-D, cameras).
Application Period
Since 14 May 2026 to 27 May 2026
[Open soon]
Centre
Robotics in Industry and Intelligent Systems