{"product_id":"kit-pi-5-sim-to-real-transfer-research-kit","title":"Pi 5 Sim-to-Real Transfer Research Kit","description":"\u003ch1\u003eBridge the Sim-to-Real Gap: Raspberry Pi 5 PPO Transfer Research Kit\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 Sim-to-Real Transfer \u0026amp; RL Deployment\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eThis kit lets you train a Proximal Policy Optimization (PPO) agent inside Nvidia Isaac Gym on your PC, then execute the same policy on a physical differential-drive robot you build around the Raspberry Pi 5. Domain randomisation techniques — varying friction, mass, timing delays — help your agent survive the reality gap, making it a complete research platform for advancing sim-to-real transfer.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a two-wheel robot with magnetic encoders for odometry, an MPU9250 IMU for orientation, and a high-speed NVMe SSD for logging training data. The final system runs a PyTorch model on the Pi 5, accepting sensor inputs and issuing motor commands in real time — a true testbed for your RL algorithms.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eSetting up a sim-to-real pipeline using Nvidia Isaac Gym and Raspberry Pi 5\u003c\/li\u003e\n  \u003cli\u003eDesigning domain randomisation strategies to bridge the reality gap\u003c\/li\u003e\n  \u003cli\u003eDeploying a PyTorch-trained PPO policy on embedded hardware for real-time control\u003c\/li\u003e\n  \u003cli\u003eTuning motor control with encoder feedback for reliable physical locomotion\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\u003eIMU MPU9250\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eDC Motor with Encoder\u003c\/td\u003e\n\u003ctd\u003e2\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\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\u003eDesigned for B.Tech (ECE, CS, AI) and M.Tech students at IITs, NITs, VIT, BITS Pilani working on reinforcement learning or robotics projects. It fits Smart India Hackathon problem statements involving autonomous robots, ATL Tinkering Lab mentors exploring advanced AI, and independent researchers who want a repeatable sim-to-real pipeline without piecemeal part sourcing.\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 launch the step-by-step AI companion, or message us on WhatsApp for direct guidance from the Compoden team.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan the Raspberry Pi 5 run RL policy inference in real time?\u003c\/summary\u003e\u003cp\u003eYes — for control loops up to ~50 Hz, the Cortex‑A76 cores handle a lightweight PyTorch model comfortably. We provide model export and ONNX optimization instructions.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes this kit include a license for Isaac Gym?\u003c\/summary\u003e\u003cp\u003eIsaac Gym is free from Nvidia for research use. The kit includes setup guides, environment examples, and domain randomisation scripts, but you’ll download the simulator separately.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat tasks can I train the robot to perform?\u003c\/summary\u003e\u003cp\u003eGoal-reaching, obstacle avoidance, and line following are great starter projects. The encoder-equipped chassis and IMU give you proprioceptive state for a wide range of locomotion policies.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003ePPO policy trained in Isaac Gym simulation on PC transferred to physical Pi 5 robot — domain randomisation for transfer.\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\/mpu6050-imu-module-6-axis-gyro-accelerometer-for-arduino\"\u003eIMU MPU9250\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/l293d-motor-driver-shield-for-arduino-drive-dc-stepper-motors\"\u003eDC Motor with Encoder\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003eCytron Motor Driver\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 Sim-to-Real Transfer Research Kit?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Pi 5 Sim-to-Real Transfer Research Kit includes all components needed: Raspberry Pi 5 8GB, IMU MPU9250, DC Motor with Encoder, Cytron Motor Driver, Robot Chassis 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 Sim-to-Real Transfer Research Kit?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 18-25. PPO policy trained in Isaac Gym simulation on PC transferred to physical Pi 5 robot — domain randomisation for transfer. Estimated build time is 10-12 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Pi 5 Sim-to-Real Transfer Research Kit online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Pi 5 Sim-to-Real Transfer Research Kit 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 Sim-to-Real Transfer Research Kit\",\n  \"description\": \"PPO policy trained in Isaac Gym simulation on PC transferred to physical Pi 5 robot — domain randomisation for transfer.\",\n  \"sku\": \"CDN-KIT-2450\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-pi-5-sim-to-real-transfer-research-kit\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"53925\",\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":53469362323821,"sku":"CDN-KIT-2450","price":62200.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-pi-5-sim-to-real-transfer-research-kit.png?v=1781948255","url":"https:\/\/compoden.com\/products\/kit-pi-5-sim-to-real-transfer-research-kit","provider":"Compoden","version":"1.0","type":"link"}