Autonomous 2D LiDAR Mobile Robot

@tshibsamuel477

Hi there, I have carefully reviewed your requirements for turning the existing Raspberry Pi 5, YDLIDAR X2, motor drivers, and encoder-based mobile base into a fully autonomous indoor robot with mapping, localisation, navigation, obstacle handling, and a simple operator interface. My background in mechatronics, robotics, embedded systems, ROS 2, LiDAR integration, motor control, odometry, SLAM, and autonomous navigation is well suited to this project. I have worked with the main technologies involved, including 2-D LiDAR mapping, differential-drive robots, encoder feedback, ROS 2 Nav2, SLAM Toolbox, Raspberry Pi, web-based interfaces, and motor-controller integration. I can implement the complete software stack: reliable map creation, stored-point navigation, localisation, obstacle avoidance/recovery, battery and charging-state handling, buzzer/LED status logic, command locking during movement, and the item-collected workflow. The system can operate completely on your local intranet without requiring internet access. Since your core hardware is already available, I can focus directly on integration, tuning, and testing and move quickly toward a reliable autonomous prototype. Send me a message with your current Raspberry Pi software, motor wiring, and encoder details, and I can start immediately. Best regards, Samuel tshibangu

@shadabkhan92

Having extensively worked on projects involving Arduino, Raspberry Pi, and robotics, I am confident that I have the skillset and experience required to successfully complete your autonomous 2D LiDAR Mobile Robot project. With a deep understanding of C Programming and Embedded Systems, I can proficiently utilize your existing hardware components while ensuring minimal modifications. Additionally, as an adept problem solver familiar with similar projects combining AI and hardware, I can navigate potential hurdles with ease. Whether it is building a reliable indoor map using SLAM, implementing localisation and path-planning for customized routes or creating a user-friendly interface that operates across multiple platforms (Android APK or a browser) to control the robot, I can deliver. What differentiates me from others is my extensive experience in marrying AI with hardware and my commitment to provide clear build/run instructions accompanied by impeccable source code. I guarantee not only the successful completion of your project but also enable you to reproduce the same results on identical hardware configurations while maintaining autonomy. Hire me today for a cutting-edge bot that efficiently moves, detects obstacles autonomously as well as provides real-time feedback on wifi connectivity and battery status!

@bojans9

Hello, I'm a Senior Software Developer | AI & Cloud with 8+ years of experience working with Robotics, Raspberry Pi and Embedded Systems. I understand you need the existing Raspberry Pi 5 + YDLIDAR X2 robot to map an indoor area, localise itself, navigate stored points and expose a simple offline UI. The real challenge is coordinating SLAM, localisation, obstacle recovery and motor control while enforcing your command-lock and charging rules. A common issue: navigation works normally but fails when localisation is lost or an obstacle blocks the route. My approach: first, connect LiDAR, encoders and motor control and validate mapping. Then, implement localisation, point navigation and the Raspberry Pi UI. Finally, test obstacle, low-battery, charging and item-collection states end-to-end. I've worked with Raspberry Pi and embedded systems, so I watch for state conflicts between navigation and safety conditions. A few questions to better understand the scope: Q1 - Which motor controller interface is available from the BTS7960 setup? This determines the cleanest control layer. Q2 - Do you already have battery-voltage sensing wired to the Pi? I recommend reading it directly for low-battery logic. Q3 - Should the UI be browser-based? I recommend this for the intranet-only setup, avoiding APK maintenance. Happy to go over the details here in chat and suggest the best approach. Looking forward to hearing from you.

@alluankit01

Hi, I can build the complete autonomy software stack for your Raspberry Pi 5 + YDLIDAR X2 mobile robot while keeping hardware changes minimal. I can handle: • ROS 2 integration with YDLIDAR X2 • SLAM mapping and saved-map management • Localization and autonomous point-to-point navigation • Nav2 path planning, obstacle avoidance, recovery, and replanning • Encoder-based differential-drive motor control for BTS7960 • Browser-based local UI accessible over intranet Wi-Fi • Live robot pose displayed on the map • Stored destination buttons and command locking while moving • “Item collected” confirmation before accepting the next command • Battery monitoring, low-battery alerts, and automatic return to a predefined point • Charging detection with navigation lockout • Buzzer/LED status logic • Offline operation with no internet dependency • Startup services, logging, configuration, and documentation I’ll structure the system with clear robot states: IDLE → NAVIGATING → ARRIVED → WAITING_FOR_COLLECTION, plus LOW_BATTERY and CHARGING modes. I’m comfortable with Raspberry Pi, ROS/ROS2, SLAM, LiDAR, Nav2, Python/C++, motor control, encoders, and web-based robot interfaces. I can develop remotely and guide hardware testing/parameter tuning on your existing robot. Best regards Ankit

@Jennycreation

Hello Sir, I have already worked on similar types of website and software development projects and I am confident that I can successfully handle your project. I am a full-time freelancer with **17+ years of experience** in web development, software development, automation, and API integrations. My expertise includes: * Android app development * ASP.NET C# web and software development * Python automation and web scraping (Amazon, Instagram, Facebook, Google Maps, LinkedIn, Telegram, and other custom scraping solutions) * JavaScript, jQuery, AJAX, Bootstrap, HTML5 * Microsoft SQL Server database development * Payment gateway integration * SMS, Email, Banking, Financial, and Insurance API integration * Custom automation bots and workflow automation software I focus on delivering **high-quality, scalable, and reliable solutions** with clean code and long-term support. Please contact me in private chat so we can discuss your requirements in detail. I can also show you a **demo of similar projects** I have completed. Looking forward to working with you. Thanks & Regards

@DeMit19

Your hardware is already a solid base, so the main work is building a reliable autonomy stack around the YDLIDAR X2, Raspberry Pi 5, encoders, and BTS7960 motor control. I can structure this around ROS 2 with SLAM, localisation, Nav2 path planning, obstacle recovery, stored destination points, and a lightweight intranet-only web UI. The UI can show pose, WiFi and battery status, lock new commands while moving or charging, and require item collection confirmation before accepting the next task. Battery return-to-point logic, buzzer/LED states, charging lockout, blocked-path recovery, and motor-controller integration will be handled as part of the navigation state machine. I would start with mapping and motor calibration, then navigation, UI, and final hardware testing.

@UzeeTech

Hello, I can turn your existing Raspberry Pi, motor drivers and 2D LiDAR into a reproducible autonomous indoor robot. • Build a reliable SLAM map and persist named destinations • Implement localization, path planning, obstacle/blocked-path recovery and safe motor control • Provide a lightweight Android/browser interface to select a point, monitor state and send commands • Keep hardware changes to zero where possible; add clear setup, build/run instructions and source code for identical hardware • Validate navigation and recovery on the supplied chassis, with logs for diagnosis I have 9 years’ full-stack experience with React.js, Node.js, Python, Flutter and AI/ML; Python robotics tooling, real-time interfaces and embedded integration are especially relevant. I will keep the control path fail-safe and documented. Which ROS/SLAM stack and LiDAR model are already installed, and should the first interface be Android or browser-based?

@hexabitzprojects

Hi, I can develop the **complete autonomous navigation stack** for your existing Raspberry Pi 5 + YDLIDAR X2 platform while keeping hardware changes to a minimum. I have **16 years of embedded/robotics experience** with Raspberry Pi, STM32, ESP32, motor control, encoders, LiDAR/sensors and industrial automation. I’ve worked on robotic motion-control systems and autonomous embedded platforms, so the motor-control and state-machine side is familiar. For your hardware, I would build around **ROS 2 + SLAM Toolbox + Nav2**. This is a proven architecture for 2D LiDAR mapping, localization, path planning and recovery behaviors. ([Nav2 Docs][1]) The system will include: * Saved indoor map + predefined destinations * Autonomous navigation and dynamic obstacle avoidance * Lost-localization/blocked-path recovery * Live map, pose, Wi-Fi and battery status UI * Browser/Android-accessible intranet interface * One-command-at-a-time state machine * **Item Collected** confirmation before next command * Movement buzzer/LED indication * Low-battery warning and automatic return to predefined location * Charging detection that disables commands and shows **Charging in Progress** I’ll integrate the existing **encoders, BTS7960 drivers, YDLIDAR X2 and Raspberry Pi 5** without adding sensors unless testing proves one is necessary. Best regards, Subhash Suman Robotics | Raspberry Pi | LiDAR | SLAM | Motor Control

@Cruz1217

Hi, integrating a 2D LiDAR stack on a Raspberry Pi 5 requires careful power management to prevent brownouts during heavy sensor processing. I would set up a ROS2 environment with SLAM to build the map and use a local web server to handle the UI requests from your Android device. This approach keeps the code lightweight and ensures the robot responds instantly to your touch commands. A common mistake is relying on the battery voltage alone for state detection, which can lead to false positives during heavy load. I will implement a current-sensing check to confirm the robot is actually charging before accepting any commands. You will get a clean, documented codebase that runs on your specific hardware without needing extra boards.

@alfatrade2

A 2-D LiDAR with no wheel encoders or IMU makes SLAM drift badly, and you ruled out new sensors, so the first thing I'd check is what odometry your motor drivers can actually give. I haven't shipped SLAM on a Pi before, but I've written microcontroller firmware for sensors and drive control in C/C++. Do your motors have encoders?

@InjectAI

I can do this project. I have hands-on experience with Raspberry Pi, robotics, ROS/Gazebo, LiDAR-based navigation concepts, motor control, and autonomous robot systems. I have also worked with PX4, simulation, sensors, and embedded AI, so I understand the full robotics workflow from sensing to navigation and control. For your existing hardware, I would build the stack around ROS 2 with the YDLIDAR X2, encoder feedback, and Raspberry Pi 5, keeping hardware changes to a minimum. My approach: * 2D LiDAR SLAM and persistent indoor map * Robot localization and autonomous navigation to saved points * Obstacle detection, waiting, recovery, and alternate path planning * Motor controller interface using the existing BTS7960/encoder setup * Local WiFi-only web UI accessible from Android or browser * Live pose, map, battery, WiFi and robot status * Command locking while moving or awaiting item collection * Collection confirmation before accepting the next task * Low-battery warning and automatic return to predefined location * Charging detection with command lock and clear charging status * Buzzer/LED states for navigation, warnings, arrival and faults Deliverables will include complete source code, Raspberry Pi setup, UI, configuration files, build/run instructions, and testing documentation.

@rajt991

Hi, I have experience with Raspberry Pi, ROS, LiDAR integration, SLAM, autonomous navigation, localization, and path planning. I can build the complete autonomy stack around your existing hardware while keeping hardware changes to a minimum. I can handle: * YDLIDAR X2 integration and indoor SLAM mapping * Localization and navigation to predefined map points * Automatic obstacle detection, waiting, and alternate path planning * Motor-controller communication through Raspberry Pi * Lightweight browser/Android-accessible control UI * Live robot pose, map, Wi-Fi, and battery status * Command locking while moving, charging, or awaiting item collection * Buzzer/LED indicators for movement, completion, errors, and low battery * Automatic return to a predefined location on low battery * Charging detection and command blocking for safety * Complete source code and clear build/run documentation I’ll design the system with proper recovery and safety states so the robot can handle blocked paths, localization loss, low battery, and charging conditions reliably. I’d be happy to review your current hardware setup and discuss milestones and testing. Best regards, Raj

@ArpitRahi

Hi, Our team includes a robotics/embedded engineer with C, aeronautics, and robotics development background — a strong fit for this SLAM/navigation build. New to Freelancer.com, but genuine hands-on capability here. One thing worth flagging on your recovery-behavior requirement: the trickiest part isn't detecting a blocked path — it's distinguishing "temporarily blocked, wait/retry" from "localization actually lost, need re-anchoring" — treating both the same way causes either premature failure or dangerous continued movement on bad pose estimates. I'd build these as distinct recovery states with different handling. My approach: • SLAM/mapping: Using your YDLIDAR X2 to build and persist a reliable indoor map. • Navigation: Localization + path-planning to pre-marked points, with proper obstacle detection and wait/reroute logic. • UI: Lightweight web/APK interface on the Pi 5 — pose display, navigation trigger, item-collected confirmation gating the next command. • Safety states: Low-battery buzzer/LED escalation with auto-return, charging-lockout with clear error messaging, intranet-only operation (no internet dependency). • Zero hardware changes: Software/wiring only, as specified. Deliverables: Full source, build/run instructions. Timeline: 20-25 days. Ready to discuss milestones.

@sakshamr74

I can deliver the complete autonomy stack on your existing hardware (Pi 5, YDLIDAR X2, BTS7960, quad-encoder motors) with zero new boards or sensors software, drivers, and wiring tuning only.

@drishu11

We would be happy to develop the complete autonomy and user-interface stack for your Raspberry Pi 5 based mobile robot using the existing YDLIDAR X2, encoder motors, BTS7960 drivers, battery system, and onboard display. We have extensive experience in such robotic devices and automation machines, including autonomous navigation, embedded control, sensor integration, Raspberry Pi systems, motor control, industrial automation, and software-hardware integration. We have also developed automation/robotic systems before, and relevant technical details and project experience can be shared in chat. We can implement SLAM and saved-map generation, localisation, point-to-point navigation, obstacle detection and replanning, recovery behaviours, command locking during movement, destination confirmation, low-battery return logic, charging-state interlock, buzzer/LED status indications, battery/Wi-Fi display, and a lightweight intranet-only browser or Android-accessible interface. The system can be structured around ROS2/Navigation2 or an equivalent lightweight architecture depending on Raspberry Pi performance and your motor-controller interface. Deliverables will include complete source code, configuration files, map files, UI, setup/build instructions, wiring/software notes, and testing documentation so the same system can be reproduced on identical hardware with minimal changes.

@bhavnaramsing

I recently helped a business turn a similar idea into a clean, professional solution that was built around what they actually needed. I can help you achieve the same, with a solution that is reliable, user-friendly and built around your goals. I noticed you specifically need the robot to navigate autonomously using the existing LiDAR system while implementing a lightweight UI. That’s an important part of getting this project right, and it’s something I can confidently handle. My expertise includes robotics programming, SLAM algorithms, and UI development for embedded systems. We also have 75+ 5-star reviews on similar projects and rank in the top 1% among 75 million users! I already have a few ideas for your project. Message me and I’ll share how I’d approach it. Regards, bhavnaramsing

@NEHABHAT92

With almost a decade of invaluable experience in web and mobile development, particularity in E-commerce and CMS based websites, you can trust me, Neha, to bring your 2D LiDAR Mobile Robot project to fruition. I have a deep understanding of Android and iOS platforms, Java, PHP, and MVC architecture - skills that will prove essential in the successful completion of your mission. Additionally, my proficiency in HTML5/CSS/Responsive Design is key to developing the lightweight UI that you require. Not only do I have the technical capabilities but I'm also well-versed in Raspberry Pi functionality; from ensuring robust indoor mapping (SLAM) and implementing localisation and path-planning algorithms to provide clear build/run instructions and source code. I always aim for simplicity which not only means faster implementation but also easier replication on identical hardware for you. Moreover, my team is talented at hardware/software tweaks working with minimal hardware changes. We guarantee top-notch services using accessible components recommendable from popular ecommerce sites in India while adhering to restricted internet usage as defined in your project requirements. Finally, it is important to mention that we offer 3 months of free support after delivery ensuring that your autonomy stack software remains operational as intended long-term. Hire us for a unique blend of precision development skills and thoughtful problem-solving abilities!

@OWAIS14325

Hi, I have hands-on experience with Raspberry Pi robotics, ROS/ROS2, 2D LiDAR SLAM, autonomous navigation, motor-controller integration and robot state-machine design. Your project is closely aligned with this workflow, especially the YDLIDAR + Raspberry Pi 5 architecture. I can build the complete software stack: reliable indoor SLAM/map saving, localization, waypoint navigation, obstacle detection, alternate-path/recovery behaviour and clean communication with the BTS7960/encoder motor system. I’ll keep the solution fully offline so everything operates within your intranet Wi-Fi without internet dependency. I’ll also develop the lightweight onboard/web UI showing the saved map, robot pose, Wi-Fi, battery/status, destination controls and item-collected workflow. The robot will enforce the required states: one active command at a time, destination confirmation before the next task, charging lockout, low-battery return-to-home, and clear LED/buzzer status indications. For fail-safe operation, I’ll integrate and test ultrasonic/weight/battery sensing where required and recommend commercially available components that can be sourced in India. I’ll also tune LiDAR navigation and recovery behaviour specifically for your existing chassis, motors and wheel configuration rather than adding unnecessary hardware. You’ll receive the complete source code, reproducible setup/build instructions, configuration files and a tested deployment on your actual Raspberry Pi 5 hardware.

@LeonBoshoff

Building a reliable indoor map and navigation system for your autonomous 2D LiDAR mobile robot is an exciting challenge. I have recently worked on similar projects involving SLAM, path-planning, and UI development for Raspberry Pi systems, which gives me a solid foundation to deliver what you need. Your requirement for a lightweight UI accessible via Android or a browser stood out. I understand the importance of having a user-friendly interface that allows for easy navigation and monitoring of the robot's actions. With a strong focus on practical solutions, I prioritize clear communication and reliability, ensuring that we stay aligned with your project goals. My experience in robotics and software development will help create a smooth, efficient user experience while minimizing hardware changes. What specific features do you envision for the UI? If we don’t end up working together, you’ll still gain valuable insights from my consultation. P.S I look forward to your message Leon B.