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Fukao-Nishio Lab
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A lab that builds robots that work autonomously outdoors, such as in fields and on roads.
AboutAbout the lab
Toward robots that work autonomously outdoors.
The Fukao-Nishio Lab studies field robotics, aiming to realize robots that work autonomously outdoors.
Combining AI and robotics, the lab tackles head-on the uncertainty and difficulty of real environments.
Its research targets include autonomous driving on narrow, rough roads, robots that automate work on vegetables and fruit trees, and drones that can work in harsh environments.
Emphasizing field testing and implementation, the lab moves back and forth between theory and practice, aiming for early deployment in society.
Key terms
- Field robotics
- A research field on robots that work in real outdoor environments, such as fields and roads, rather than inside factories
- Deep learning
- A machine learning method that uses neural networks with many stacked layers to learn features from large amounts of data
- LiDAR
- A sensor that shines laser light on its surroundings to measure the distance to and the shape of nearby objects
ResearchResearch themes
The lab works on field robotics, which deals with robots that operate in real outdoor environments. Its research covers autonomous driving of passenger cars, trucks, and agricultural machinery, automatic harvesting of fruits and vegetables, autonomous drone flight, and autonomous mobile robots.
*Illustrative imageAutonomous Driving of Trucks and Other Vehicles
The lab has studied a wide range of autonomous driving, including automatic parking, obstacle avoidance, truck platooning, and driving on snowy roads. Currently, it is working on small trucks driving on rural roads where the road edges are not clearly defined.
*Illustrative imageAutomatic Cabbage Harvesting
Cabbages are detected and harvested using deep learning and a camera that can also measure distance. The lab also combines automatic exchange of the containers that hold the cabbages with autonomous driving of the transport vehicle to reduce working time.
*Illustrative imageAutomatic Onion Harvesting
Onions are detected and harvested using semantic segmentation, a method that classifies an image region by region, together with a camera that can also measure distance. The tractor that runs alongside the harvester is equipped with high-precision satellite positioning and a compass.
*Illustrative imageAutonomous Vehicles for Orchards
Tree trunks are detected with deep learning and LiDAR to estimate the vehicle's position and orientation. Based on these estimates, a vehicle fitted with a mower drives itself through the orchard.
MembersFaculty
The members of the Fukao-Nishio Lab consist of faculty, technical staff, project specialist staff, and doctoral, master's, and undergraduate students.
- ProfessorFukao TakanoriPublications ↗
- ProfessorYinqiang Zheng
- LecturerTakuzumi NishioPublications ↗
- Assistant ProfessorMasaki Asano
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Autonomous compact tractors in a Texas vineyard, Nov 2012” ASIrobots / CC BY-SA 3.0 (cropped)
- Autonomous Driving of Trucks and Other Vehicles: “Butchers Lane, Aughton” Sweetie candykim / CC0 (cropped)
- Automatic Cabbage Harvesting: “Harvester in Punchbowl Lane Field - geograph.org.uk - 2521802” Josie Campbell / CC BY-SA 2.0 (cropped)
- Automatic Onion Harvesting: “Onion harvest in Bavaria 1” pfatter / CC BY 2.0 (cropped)
- Autonomous Vehicles for Orchards: “160322 Zeit für Rückschnitt” R.kaelcke / CC BY-SA 4.0 (cropped)
- Related lab (JSK研究室
（情報システム工学研究室／Jouhou System Kougaku Laboratory） （岡田研究室） ): “Ars Electronica 2008 Kotaro” Manfred Werner - Tsui / CC BY-SA 3.0 (cropped) - Related lab (ISI研究室(Intelligent Systems and Informatics Lab)
（國吉研究室） ): “Icub full body” Jll at English Wikipedia / CC BY-SA 3.0 (cropped) - Related lab (原田・黒瀬・椋田研究室(Machine Intelligence Lab/MIL)): “Ouster OS1-64 lidar point cloud of intersection of Folsom and Dore St, San Francisco” Daniel L. Lu / CC BY 4.0 (cropped)
- Related lab (竹内・ニエ研究室): “Lab on a Chip ( )” National Institute of Standards and Technology / Public domain (cropped)
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