{"id":3199,"date":"2023-10-03T15:09:23","date_gmt":"2023-10-03T15:09:23","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2023\/10\/03\/meet-the-maker-robotics-student-rolls-out-autonomous-wheelchair-with-nvidia-jetson\/"},"modified":"2023-10-03T15:09:23","modified_gmt":"2023-10-03T15:09:23","slug":"meet-the-maker-robotics-student-rolls-out-autonomous-wheelchair-with-nvidia-jetson","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2023\/10\/03\/meet-the-maker-robotics-student-rolls-out-autonomous-wheelchair-with-nvidia-jetson\/","title":{"rendered":"Meet the Maker: Robotics Student Rolls Out Autonomous Wheelchair With NVIDIA Jetson"},"content":{"rendered":"
\n

With the help of AI, robots, tractors<\/a> and baby strollers<\/a> \u2014 even skate parks<\/a> \u2014 are becoming autonomous. One developer, Kabilan KB, is bringing autonomous-navigation capabilities to wheelchairs, which could help improve mobility for people with disabilities.<\/p>\n

\"\"<\/p>\n

The undergraduate from the Karunya Institute of Technology and Sciences in Coimbatore, India, is powering his autonomous wheelchair project using the NVIDIA Jetson<\/a> platform for edge AI and robotics.<\/p>\n

The autonomous motorized wheelchair is connected to depth and lidar sensors \u2014 along with USB cameras \u2014 which allow it to perceive the environment and plan an obstacle-free path toward a user\u2019s desired destination.<\/p>\n

\u201cA person using the motorized wheelchair could provide the location they need to move to, which would already be programmed in the autonomous navigation system or path-planned with assigned numerical values,\u201d KB said. \u201cFor example, they could press \u2018one\u2019 for the kitchen or \u2018two\u2019 for the bedroom, and the autonomous wheelchair will take them there.\u201d<\/p>\n

An NVIDIA Jetson Nano Developer Kit<\/a> processes data from the cameras and sensors in real time. It then uses deep learning-based computer vision models to detect obstacles in the environment.<\/p>\n

\"\"<\/p>\n

The developer kit acts as the brain of the autonomous system \u2014 generating a 2D map of its surroundings to plan a collision-free path to the destination \u2014 and sends updated signals to the motorized wheelchair to help ensure safe navigation along the way.<\/p>\n

About the Maker<\/strong><\/h2>\n

KB, who has a background in mechanical engineering, became fascinated with AI and robotics during the pandemic, when he spent his free time searching up educational YouTube videos on the topics.<\/p>\n

He\u2019s now working toward a bachelor\u2019s degree in robotics and automation at the Karunya Institute of Technology and Sciences and aspires to one day launch a robotics startup.<\/p>\n

KB, a self-described supporter of self-education, has also received several certifications from the NVIDIA Deep Learning Institute<\/a>, including \u201cBuilding Video AI Applications at the Edge on Jetson Nano\u201d and \u201cDevelop, Customize and Publish in Omniverse With Extensions.\u201d<\/p>\n

Once he learned the basics of robotics, he began experimenting with simulation in NVIDIA Omniverse<\/a>, a platform for building and operating 3D tools and applications based on the OpenUSD<\/a> framework.<\/p>\n

\u201cUsing Omniverse for simulation, I don\u2019t need to invest heavily in prototyping models for my robots, because I can use synthetic data<\/a> generation instead,\u201d he said. \u201cIt\u2019s the software of the future.\u201d<\/p>\n

His Inspiration<\/strong><\/h2>\n

With this latest NVIDIA Jetson project, KB aimed to create a device that could be helpful for his cousin, who has a mobility disorder, and other people with disabilities who might not be able to control a manual or motorized wheelchair.<\/p>\n

\u201cSometimes, people don\u2019t have the money to buy an electric wheelchair,\u201d KB said. \u201cIn India, only upper- and middle-class people can afford them, so I decided to use the most basic type of motorized wheelchair available and connect it to the Jetson to make it autonomous.\u201d<\/p>\n

The personal project was funded by the Program in Global Surgery and Social Change, which is jointly positioned under the Boston Children\u2019s Hospital and Harvard Medical School.<\/p>\n

His Jetson Project<\/b><\/h2>\n

After purchasing the basic motorized wheelchair, KB connected its motor hub with the NVIDIA Jetson Nano and lidar and depth cameras.<\/p>\n

He trained the AI algorithms for the autonomous wheelchair using YOLO object detection on the Jetson Nano, as well as the Robot Operating System, or ROS, a popular software for building robotics applications.<\/p>\n

The wheelchair can tap these algorithms to perceive and map its environment and plan a collision-free path.<\/p>\n

\u201cThe NVIDIA Jetson Nano\u2019s real-time processing speed prevents delays or lags for the user,\u201d said KB, who\u2019s been working on the project\u2019s prototype since June. The developer dives into the technical components of the autonomous wheelchair on his blog<\/a>. A demo<\/a> of the autonomous wheelchair has also been featured on the Karunya Innovation and Design Studio YouTube channel.<\/p>\n

Looking forward, he envisions his project could be expanded to allow users to control a wheelchair using brain signals from electroencephalograms, or EEGs, that are connected to machine learning algorithms.<\/p>\n

\u201cI want to make a product that would let a person with a full mobility disorder control their wheelchair by simply thinking, \u2018I want to go there,\u2019\u201d KB said.<\/p>\n

Learn more about the <\/i>NVIDIA Jetson platform<\/i><\/a>.<\/i><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

https:\/\/blogs.nvidia.com\/blog\/2023\/10\/03\/kabilan-kb-autonomous-wheelchair\/<\/p>\n","protected":false},"author":0,"featured_media":3200,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3199"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=3199"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3199\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/3200"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=3199"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=3199"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=3199"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}