TrimBot: a gardening robot for rose, hedge and topiary trimming
Grant 688007 TrimBot2020 |
January 2016 - December 2019
Project members
Funded members:Prof. Dr. Thomas Brox
Nikolaus Mayer
Huizhong Zhou
Artemij Amiranashvili
The TrimBot2020 project
will research the robotics and vision technologies to prototype the first outdoor garden
trimming robot. The robot will navigate over varying terrain, approach rose bushes, hedges and boxwood topiary,
to trim them to an ideal shape. The robot will be based on a modified Bosch Indego robot lawnmower, which will
navigate using a user-defined garden map and 3D scene analysis, and then visually servo a novel electric plant cutter.
Achieving this requires a combination of robotics and 3D computer vision research and innovation activities.
Original developments are required for 3D sensing of semi-regular surfaces with physical texture (overgrown
plant surfaces), coping with outdoor lighting variations, self-localising and navigating over real terrain and around
obstacles, visual servoing to align the vehicle with potentially moving target plants, visual servoing to align leaf
and branch cutters to a compliant surface, and innovative engineering to deliver all this on a small battery-powered
consumer-grade vehicle. |
More details on the overall project can be found on the consortium page.
Publications related to this project
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction
Paper
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE: 5542--5549, Nov 2019
European Conference on Computer Vision (ECCV), 2018
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation
Paper
European Conference on Computer Vision (ECCV), 2018
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?
Paper
doi>
Project
International Journal of Computer Vision, 126(9): 942-960, 2018
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
Paper
doi>
Code/data
Project
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2016