{"product_id":"kit-pi-5-uncertainty-aware-robot-navigation","title":"Pi 5 Uncertainty Aware Robot Navigation","description":"\u003ch1\u003ePi 5 Uncertainty Aware Robot Navigation — A Bayesian Neural Network on Wheels\u003c\/h1\u003e\n\n\u003cp class=\"value-summary\"\u003eEvery part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.\u003c\/p\u003e\n\n\u003cdiv class=\"specs-strip\"\u003e\n  \u003cspan\u003e\u003cstrong\u003eDifficulty:\u003c\/strong\u003e Advanced\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 10–12 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 18–25\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Embedded Bayesian AI for motion planning\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eYour robot will see obstacles through a Pi Camera and RPLidar, then run a Bayesian neural network right on the Pi 5 to estimate how confident it is in those detections. When the model is uncertain — say, a cluttered corner or a reflective surface — the planner automatically slows down and takes a wider, safer path. This isn’t just obstacle avoidance; it’s risk‑aware navigation built for academic research, Smart India Hackathon prototypes, and final‑year engineering projects.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eAn autonomous ground robot that fuses camera and lidar data, quantifies uncertainty with a Bayesian neural network, and generates conservative motion plans in real time. The robot maps its indoor environment, labels risk zones, and drives a chassis with differential steering, all while logging uncertainty maps to the onboard SSD. You’ll have a fully functional platform that demonstrates AI‑driven decision‑making under uncertainty — ideal for B.Tech demonstrations, IEEE papers, or lab‑scale experiments.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy a Bayesian neural network on Raspberry Pi 5 for real‑time inference\u003c\/li\u003e\n  \u003cli\u003eFuse lidar point clouds with camera images to build richer obstacle representations\u003c\/li\u003e\n  \u003cli\u003eConvert model uncertainty scores into actionable path planning constraints\u003c\/li\u003e\n  \u003cli\u003eIntegrate motor control, sensor drivers, and an NVMe storage stack into a coherent robotics pipeline\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eKit Contents\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eComponent\u003c\/th\u003e\n\u003cth\u003eQuantity\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRaspberry Pi 5 8GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRPLidar A1\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 3\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCytron Motor Driver\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eDC Motor\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRobot Chassis\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNVMe SSD 512GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi 5 M.2 HAT+\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eUSB-C PSU\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eM-M Wires\u003c\/td\u003e\n\u003ctd\u003e20\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWhy Buy This Kit Instead of Sourcing Parts Separately\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eFactor\u003c\/th\u003e\n\u003cth\u003eSourcing Separately\u003c\/th\u003e\n\u003cth\u003eCompoden Kit\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCompatibility checks\u003c\/td\u003e\n\u003ctd\u003eYou verify every part\u003c\/td\u003e\n\u003ctd\u003ePre-tested as a system\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eBuild support\u003c\/td\u003e\n\u003ctd\u003eForums and scattered tutorials\u003c\/td\u003e\n\u003ctd\u003eAI companion trained on this exact project\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTime to first working build\u003c\/td\u003e\n\u003ctd\u003eDays of debugging\u003c\/td\u003e\n\u003ctd\u003eHours, with step-by-step guidance\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eShipping coordination\u003c\/td\u003e\n\u003ctd\u003eMultiple sellers, multiple delays\u003c\/td\u003e\n\u003ctd\u003eOne shipment from Bengaluru in 3-5 days\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWho This Kit Is For\u003c\/h2\u003e\n\u003cp\u003eB.Tech ECE, EEE, and CSE students tackling final‑year projects or Smart India Hackathon challenges will find this kit immediately relevant. M.Tech researchers working on uncertainty quantification in robotics can skip hardware integration and jump straight into algorithm refinement. ATL Tinkering Labs at IITs, NITs, VIT, and BITS Pilani now have a reproducible, high‑level reference design for AI robotics workshops.\u003c\/p\u003e\n\n\u003ch2\u003eBuilt and Backed by Compoden\u003c\/h2\u003e\n\u003cp\u003eEvery Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.\u003c\/p\u003e\n\n\u003cdetails\u003e\u003csummary\u003eWhat if I get stuck during the build?\u003c\/summary\u003e\u003cp\u003eScan the QR code to open the AI companion; it recognises your exact kit and can troubleshoot step by step. If you need human help, send a photo on WhatsApp and our team will respond within a few hours.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan this robot handle outdoor terrains?\u003c\/summary\u003e\u003cp\u003eThe RPLidar A1 and chassis are designed for indoor flat surfaces only. For outdoor rough‑terrain navigation, additional sensory hardware and a different locomotion platform would be required.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need to train the Bayesian neural network from scratch?\u003c\/summary\u003e\u003cp\u003eNo. A pre‑trained model is included on the SSD, ready to run. You can fine‑tune it with your own data using the provided scripts and logging framework.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I add a depth camera like Intel RealSense later?\u003c\/summary\u003e\u003cp\u003eYes. The software pipeline is modular; you can integrate additional sensors via the ROS2 drivers pre‑installed on the Pi 5, and the uncertainty estimation module will accept new input modalities.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eBayesian neural network on Pi 5 quantifies uncertainty in obstacle detection — robot plans conservative paths when uncertain.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-5-model-b-8gb-high-performance-single-board-computer\"\u003eRaspberry Pi 5 8GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/rplidar-a1-360-laser-scanner-for-robotics-slam-compoden\"\u003eRPLidar A1\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/4-channel-relay-board-for-esp32-30-pin-5v-control\"\u003ePi Camera Module 3\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eCytron Motor Driver\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/l293d-motor-driver-shield-for-arduino-drive-dc-stepper-motors\"\u003eDC Motor\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/2-wheel-smart-car-robot-chassis-kit-diy-for-arduino-raspberry-pi\"\u003eRobot Chassis\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/official-raspberry-pi-m2-hat-nvme-ssd-add-on-board-for-pi-5\"\u003eNVMe SSD 512GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-5-pcie-to-m2-nvme-ssd-expansion-board-by-elecrow\"\u003ePi 5 M.2 HAT+\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-4-official-power-supply-5v-3a-usb-c-compoden\"\u003eUSB-C PSU\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eM-M Wires x20\u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is included in the Pi 5 Uncertainty Aware Robot Navigation?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Pi 5 Uncertainty Aware Robot Navigation includes all components needed: Raspberry Pi 5 8GB, RPLidar A1, Pi Camera Module 3, Cytron Motor Driver, DC Motor and more. Everything is pre-tested for compatibility and shipped from Bengaluru, India.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What skill level is required for the Pi 5 Uncertainty Aware Robot Navigation?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 18-25. Bayesian neural network on Pi 5 quantifies uncertainty in obstacle detection — robot plans conservative paths when uncertain. Estimated build time is 10-12 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Pi 5 Uncertainty Aware Robot Navigation online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Pi 5 Uncertainty Aware Robot Navigation is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. Ships from Bengaluru in 1-5 business days across India.\"\n      }\n    }\n  ]\n}\n\u003c\/script\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Product\",\n  \"name\": \"Pi 5 Uncertainty Aware Robot Navigation\",\n  \"description\": \"Bayesian neural network on Pi 5 quantifies uncertainty in obstacle detection — robot plans conservative paths when uncertain.\",\n  \"sku\": \"CDN-KIT-2461\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-pi-5-uncertainty-aware-robot-navigation\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"64550\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"AI Robotics\"\n}\n\u003c\/script\u003e","brand":"Compoden","offers":[{"title":"Default Title","offer_id":53469363077485,"sku":"CDN-KIT-2461","price":74740.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-pi-5-uncertainty-aware-robot-navigation.png?v=1781948273","url":"https:\/\/compoden.com\/products\/kit-pi-5-uncertainty-aware-robot-navigation","provider":"Compoden","version":"1.0","type":"link"}