Gazebo Plants: Simulating Plant-Robot Interaction with Cosserat Rods
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909092981768192 |
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| author | Deng, Junchen Marri, Samhita Klein, Jonathan Pałubicki, Wojtek Pirk, Sören Chowdhary, Girish Michels, Dominik L. |
| author_facet | Deng, Junchen Marri, Samhita Klein, Jonathan Pałubicki, Wojtek Pirk, Sören Chowdhary, Girish Michels, Dominik L. |
| contents | Robotic harvesting has the potential to positively impact agricultural productivity, reduce costs, improve food quality, enhance sustainability, and to address labor shortage. In the rapidly advancing field of agricultural robotics, the necessity of training robots in a virtual environment has become essential. Generating training data to automatize the underlying computer vision tasks such as image segmentation, object detection and classification, also heavily relies on such virtual environments as synthetic data is often required to overcome the shortage and lack of variety of real data sets. However, physics engines commonly employed within the robotics community, such as ODE, Simbody, Bullet, and DART, primarily support motion and collision interaction of rigid bodies. This inherent limitation hinders experimentation and progress in handling non-rigid objects such as plants and crops. In this contribution, we present a plugin for the Gazebo simulation platform based on Cosserat rods to model plant motion. It enables the simulation of plants and their interaction with the environment. We demonstrate that, using our plugin, users can conduct harvesting simulations in Gazebo by simulating a robotic arm picking fruits and achieve results comparable to real-world experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_02570 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Gazebo Plants: Simulating Plant-Robot Interaction with Cosserat Rods Deng, Junchen Marri, Samhita Klein, Jonathan Pałubicki, Wojtek Pirk, Sören Chowdhary, Girish Michels, Dominik L. Robotics Machine Learning I.6.3; I.6.m Robotic harvesting has the potential to positively impact agricultural productivity, reduce costs, improve food quality, enhance sustainability, and to address labor shortage. In the rapidly advancing field of agricultural robotics, the necessity of training robots in a virtual environment has become essential. Generating training data to automatize the underlying computer vision tasks such as image segmentation, object detection and classification, also heavily relies on such virtual environments as synthetic data is often required to overcome the shortage and lack of variety of real data sets. However, physics engines commonly employed within the robotics community, such as ODE, Simbody, Bullet, and DART, primarily support motion and collision interaction of rigid bodies. This inherent limitation hinders experimentation and progress in handling non-rigid objects such as plants and crops. In this contribution, we present a plugin for the Gazebo simulation platform based on Cosserat rods to model plant motion. It enables the simulation of plants and their interaction with the environment. We demonstrate that, using our plugin, users can conduct harvesting simulations in Gazebo by simulating a robotic arm picking fruits and achieve results comparable to real-world experiments. |
| title | Gazebo Plants: Simulating Plant-Robot Interaction with Cosserat Rods |
| topic | Robotics Machine Learning I.6.3; I.6.m |
| url | https://arxiv.org/abs/2402.02570 |