Active Perception in Autonomous Fruit Harvesting: Viewpoint Optimization with Deep Reinforcement Learning

This MSc thesis presents the development of a viewpoint optimization framework to face the problem of detecting occluded fruits in autonomous harvesting. A Deep Reinforcement Learning (DRL) algorithm is developed in order to train a robotic manipulator to navigate to occlusion-free viewpoints of the tomato-target. Two Convolutional Neural Networks (CNN), You Only Look Once (YOLO) version 3 and Mask Regional Convolutional Neural Network (Mask R-CNN), are trained and evaluated in order to obtain visual information from the tomatoes. The two trained CNN achieve high detection accuracy and surpass other fruit detection methods. The instance segmentation Mask R-CNN result and an image processing algorithm are applied in an occlusion modelling method. The vision-based reward formulation for the DRL algorithm is closely related to the occlusion modelling metric. The DRL algorithm is trained and evaluated in a simulation environment by mounting a camera on a robotic arm. The use of different reward scheme and exploration strategy during DRL training shows their effect on training performance. The DRL training performance is assessed by illustrating the maximum visible tomato-target fraction per episode, the steps needed per episode, the trajectory of the robot's end-effector, and the initial and final tomato-target viewpoint in each episode. The evaluation results show a satisfactory performance, which depends on the reward and exploration strategy, as in the majority of the cases the robot can fully see the tomato-target after a few steps.Mechanical Engineering | Process and Energy Technolog

Inner ionian archipelagos and adjacent gulfs: ecological mapping for the needs of ecosystem-based marine spatial

Mapping of ecosystem components (natural and socioeconomic) is a prerequisite for ecosystem-based marine spatial management (EB-MSM). To initiate the process of EB-MSM in the Inner Ionian Archipelagos and adjacent gulfs, the main relevant ecosystem components were mapped based on existing spatial information and expert judgment. The natural components mapped included habitat types and species of conservation importance, according to national and European legislation and international agreements. Main human activities/pressures related to fisheries, aquaculture, tourism, and industry were also mapped. A substantial overlapping between ecological features and human activities was identified, confirming the need for a well planned approach of managing marine space in order to mitigate conflicts for marine resources and to conserve marine ecosystems and their associated goods and services.JRC.H.1-Water Resource

Ecological mapping and data quality assessment for the needs of ecosystem-based marine spatial management: case study Greek Ionian Sea and the adjacent gulfs

Mapping of ecosystem components (natural and socioeconomic) is a prerequisite for ecosystem-based marine spatial management (EB-MSM). To initiate the process of EB-MSM in the Greek Ionian Sea and the adjacent gulfs, the main relevant ecosystem components were mapped based on existing spatial information and expert judgment. The natural components mapped included habitat types and species targeted for conservation, according to national and European legislation and international agreements. Main human activities/pressures related to fisheries, aquaculture, tourism, and industry were also mapped. In order to assess the quality of data used to map ecosystem components and therefore take into consideration the inherent uncertainty, an assessment of 5 semi-quantitative data indicators based on a pedigree matrix was conducted. Through this qualitative approach we gained information related to the sources, acquisition and verification procedures, statistical properties, and temporal & geographical correlation, along with the collection process quality of the ecosystem components under study. A substantial overlapping between ecological features and human activities was identified, confirming the need for a well-planned approach to marine space management, in order to mitigate conflicts for marine resources and conserve marine ecosystems and their associated goods and services.JRC.H.1-Water Resource