Cette solution est à l’étude pour éviter aux gestionnaires de jardins et autres espaces verts d’avoir recours à des désherbants chimiques tels que le glyphosate toujours toxiques pour les utilisateurs.
Des chercheurs de l’Université du Texas ont mis au point un lance-flammes propane-butane contrôlé par un bras robotique, le tout porté par un robot dit Spot de Boston Dynamics
La solution sera peut-être à éviter dans les périodes de sécheresse dues au réchauffement climatique
Spot est un peu semblable à un chien dont il possède l’agilité
Spot de Boston Dynamics https://bostondynamics.com/products/spot/
Référence
https://arxiv.org/abs/2407.04929
[Submitted on 6 Jul 2024]
Toward Precise Robotic Weed Flaming Using a Mobile Manipulator with a Flamethrower
Authors Di Wang, and others
Robotic weed flaming is a new and environmentally friendly approach to weed removal in the agricultural field. Using a mobile manipulator equipped with a flamethrower, we design a new system and algorithm to enable effective weed flaming, which requires robotic manipulation with a soft and deformable end effector, as the thermal coverage of the flame is affected by dynamic or unknown environmental factors such as gravity, wind, atmospheric pressure, fuel tank pressure, and pose of the nozzle. System development includes overall design, hardware integration, and software pipeline. To enable precise weed removal, the greatest challenge is to detect and predict dynamic flame coverage in real time before motion planning, which is quite different from a conventional rigid gripper in grasping or a spray gun in painting. Based on the images from two onboard infrared cameras and the pose information of the flamethrower nozzle on a mobile manipulator, we propose a new dynamic flame coverage model. The flame model uses a center-arc curve with a Gaussian cross-section model to describe the flame coverage in real time. The experiments have demonstrated the working system and shown that our model and algorithm can achieve a mean average precision (mAP) of more than 76\% in the reprojected images during online prediction.
Europe Solidaire 