Description
- ROS2 & High-Performance HardwareROSOrin runs on ROS2, compatible with Jetson and Raspberry Pi. It features LiDAR, a 3D camera, and a six-microphone array for tasks like mapping and navigation, 3D recognition, and voice interaction.
- Multimodal Large AI ModelROSOrin integrates a ChatGPT-based AI model for advanced embodied AI applications, such as environment perception, task planning, and autonomous driving.
- Versatile Chassis ExpansionSwitches between Mecanum, Ackermann, and differential drive chassis, paired with a swing arm suspension system for stable movement and precise control on complex terrains.
- AI Vision Algorithms Equipped with YOLOv11, OpenCV, MediaPipe, and KCF algorithms, ROSOrin delivers powerful visual perception for advanced applications like autonomous driving, face recognition, and target tracking.
- Learning Resources Includes comprehensive tutorials, source code, and AI project examples from beginner to advanced, everything needed to move from first build to advanced ROS applications.
Product Description
Hiwonder ROSOrin is a multimodal AI robot developed on ROS2. It features a modular chassis design that allows fast switching between Mecanum, Ackermann, and differential drive chassis, enabling flexible adaptation to diverse scenarios. ROSOrin robot is equipped with high-performance hardware including NVIDIA Jetson, Raspberry Pi 5, LiDAR, 3D depth camera, and an integrated 6-microphone array. It easily supports motion control, mapping and navigation, path planning, 3D perception, tracking and obstacle avoidance, object recognition, target tracking, gesture interaction, and voice interaction. ROSOrin deploys a multimodal large AI model that combines AI vision and LiDAR sensing to understand environments, plan actions, and execute tasks autonomously. It enables advanced embodied intelligence applications and is an ideal platform for learning ROS development and AI robotics.
1) AI Voice Interaction
Hiwonder ROSOrin senses emotions and responds to your voice with feedbacks and actions through embodied intelligence, making interactions feel natural and friendly.
2) Multimodal AI Integration
ROSOrin combines advanced AI for text, voice, and vision, delivering powerful cognition for natural conversations and smart visual understanding.
3) AI Vision & Tracking
With built-in OpenCV vision algorithms, ROSOrin can quickly identify colors and objects, calculate their positions in real time, and track them accurately.
4) Built-in AI Vision Algorithms
With YOLOv11, MediaPipe, and OpenCV, ROSOrin handles object detection, face recognition, and gesture control with no complex setup required.
5) 3D Depth Camera
The 3D depth camera can not only realize AI visual game-play, but also enable advanced gameplay such as depth image data processing and 3D visual mapping navigation.
6) MS200 TOF Lidar
ROSOrin is equipped with Lidar, which can realize SLAM mapping and navigation, and supports path planning, fixed-point navigation and dynamic obstacle avoidance.
7) Jetson Control System
Jetson allows you to run multiple neural networks, object detection, segmentation and speech processing applications in parallel.
8) 6-Ch Far-field Microphone Array
The 6-Ch far-field microphone array and speakers support sound source positioning, voice recognition control, voice navigation and other functions.
1. Why Choose ROSOrin? – A professional Al education robot designed for ROS developers.
1) Versatile 3-in-1 Chassis
Featuring an integrated modular chassis, ROsOrin supports quick switching between Mecanum, Ackermann, and differential drive chassis. It enables seamless transitions across diferent scenarios, ensures stable and efficient movement, and fully meets the learning and validation needs of multimodal robotics.
2) Multimodal Large Al Model
ROsorin deploys a multimodal Al model combining language,voice, and vision.Integrated with Al vision and LiDAR, it enables Rosorin to better perceive its surroundings and understand commands, unlocking advanced embodied intelligence and creative applications.
3) Extensive ROS Development Projects
ROsorin ofers multiple controller options and supports LiDAR mapping,navigation, and path planning. It integrates visual algorithms such as YOLOv11, Mediapipe, KCF, and OpenCV, enabling a variety of Al vision recognition, visual interaction, and other Al-powered projects.
4) 3-in-1 MultiModal Chassis
ROsorin features a modular chassis design, supporting fast switching between Mecanum, Ackermann, and dfferential drive chassis for flexible multimodal transitions. Equipped with a swing arm suspension system, it ensures stable and efficient operation on complex terrains.
Mecanum wheel chassis, 360 omnidirectional movement
The Mecanum Wheel is a classic type of omnidirectional wheel. By coordinating the speed and direction of individual wheels, it can generate thrust in any direction, enabling the chassis to achieve full planar motion.
Ackermann chassis, front wheel steering
The Ackermann steering structure is the standard design usedin modern vehicle chasis. During turning, the front wheels steer at different angles to accommodate the inner and outer wheel paths. Its precise design makes it highly suitable for efficient ROs-based robotics learning and research.
Four-Wheel Differential Chassis
The four-wheel differential chassis uses independent drive for the left and right wheels, controlling their speed difference to move forward, backward, steer,and rotate in place. Equipped with high-quality rubber tires,it delivers strong grip and long-lasting durability.
2. Multimodal Large Model Deployment
ROSOrin integrates a Multimodal Large Al Model and supports online deployment via OpenAl’s API, enabling real-time access to advanced Al capabilities. It also allows seamless switching to alternative models, such as those available through OpenRouter, to support Vision Language Model applications. At its core, ROsOrin is designed as an all-in-one interaction hub built around ChatGPT, enabling sophisticated embodied Al use cases and creating a smooth, intuitive human-machine interaction experience!
Large Speech Model
Empowered by a 6-microphone array, ROsOrin now has “ears” and a “voice”, enabling it to hear your voice and respond in real time. Powered by advanced end-to-end streaming speech language modeling and natural language processing, it offers smooth and natural voice interaction.
Large speech Model
Empowered by a 6-microphone array, ROSOrin now has “ears”and a “voice”, enabling it to hearyour voice and respond in realtime. Powered by advanced end-to-end streaming speech-language modeling and natural language processing, it offers smooth and natural voice interaction.
Vision Language Model
ROSOrin integrates with OpenRouter’s vision language model, enabling advanced image understanding and analysis. It can accurately identify and locate objects within complex visual scenes, while also delivering detailed descriptions that cover object names, characteristics, and other relevant attributes.
3. Integration of Large AI Model with SLAM-Based Mapping and Navigation
ROSOrin combines multimodal large model to understand user voice commands via a large language model, enabling multi-point navigation. Once it arrives at the designated location, it uses a vision language model to gain a deep understanding of the surrounding objects and events. This approach greatly enhances the robots intelligence, adaptability, and overall user experience, making it better suited to meet real-world needs.
1) Environmental Perception
Powered by a vision language model, ROSOrin AI robot can interpret objects in its surroundings and understand the spatial layout of the environment.
2) Semantic Understanding
With semantic understanding capabilities, Hiwonder ROSOrin can accurately capture key intents in text and speech, deeply analyzing context, sentiment, and hidden requirements.
3) Image Analysis
ROSOrin leverages a visual AI model to deeply analyze images and real-time frames, extract object features, and match them precisely with the database, enabling multi-object localization and similar-object association.
4) Intelligent Navigation
ROSOrin continuously sends environmental data to the vision language model for real-time in-depth analysis. It dynamically adjusts its navigation path based on user voice commands, allowing it to autonomously navigate to designated areas and deliver intelligent, adaptive routing.
5) Complex Task Management
ROSOrin integrates visual understanding, speech recognition, and SLAM path planning to break down complex instructions, perceive the environment in real time, and execute recognition, tracking, and other operations seamlessly.
6) Emotion Perception
Leveraging an extended RAG knowledge base, ROSOrin can recognize intent and analyze environmental context, anticipating potential needs without detailed instructions, autonomously planning tasks and responding dynamically.
4. Large AI ModelDriven Embodied AI Applications
ROSOrin Kit are equipped with a circular 6-microphone array. Going beyond the one-way command-response pattern of traditional AI models, ROSOrinpowered by ChatGPTenables a cognitive leap from semantic understanding to physical execution, significantly enhancing the naturalness and fluidity of human-machine interaction. Combined with advanced machine vision, ROSOrin delivers outstanding capabilities in perception, reasoning, and action, making it ideal for developing sophisticated embodied AI applications.
1) Vision Tracking
With the advanced perception capabilities of a vision language model, ROSOrin can intelligently identify and lock onto target objects even in complex environments, allowing it to perform real-time tracking with adaptability and precision.
2) Voice Control
With ChatGPT integration, ROSOrin can comprehend spoken commands and carry out corresponding actions, enabling intuitive and seamless voice-controlled interaction.
3) Autonomous Patrolling
Utilizing semantic understanding from a large language model, ROSOrin can accurately detect and track lines of various colors in real time while autonomously navigating obstacles, ensuring smooth and efficient patrolling.
4) Distance Awareness
Hiwonder ROSOrin car combines a visual AI model with a depth camera to understand its environment and perceive distances. By combining visual recognition with distance data, it enables intelligent question answering.
5. Key ROS Features
1) Lidar Mapping Navigation
ROSOrin features a high-precision LiDAR and combines encoder and IMU data for accurate mapping and autonomous navigation. It supports multiple mapping algorithms, single-point and multi-point navigation, and can be controlled via an app.
Cartographer LiDAR Mapping
Hector LiDAR Mapping
slam_toolbox LiDAR Mapping
Gmapping LiDAR Mapping
IMU-LiDAR Fusion & Filtering
TEB Path Planning & Dynamic Obstacle Avoidance
RRT Autonomous Exploration & Mapping
Single-Point/Multi-Point Navigation
Multi-Point Navigation
LiDAR ObstacleAvoidance
2) 3D Depth Camera Function
The 3D structured-light depth camera can generate depth maps and point cloud data, accurately measuring the distance and volume of target objects. Combined with LiDAR data, it can build 3D color maps, providing more precise support for environmental perception and intelligent navigation.
Depth Data & Point Cloud
Depth Camera Distance Measurement
ORBSLAM2+ORBSLAM3
RTAB-Map 3D Visual Mapping & Navigation
3) YOLOv11 Model Detection
ROSOrin features a built-in YOLOv1 1 deep learning model, supporting image seqmentation, pose estimation, image clasification, and targeted object detection. Complete tutorials for model training and deployment are also provided.
lmage Segmentation
Pose Estimation
Image Classification
Object Detection
4) Al Vision Interaction Features
ROsorin combines computer vision algorithms with motion control strategies to enable real time target detection and locking via the pan-tilt mechanism. With the depth camera, it further incorporates distance sensing to achieve 3D intelligent following in space.
Color Tracking
Face Tracking
QR Code Control
Line Following
MediaPipe Pose
KCF Object Tracking
Deep Learning
Gesture Control
Detection
Target Tracking
5) Remote Voice Pickup & Sound Source Localization
Equipped with a 6-mic array, RosOrin delivers accurate sound localization and effective noise reduction. When paired with LiDAR, it enables voice-based positioning and smart navigation. With iFlytek cloud dialogue, a single spoken command can control the robot or guide it through the mapped environment.
Natural Voice Interaction
Intelligent Voice Navigation
360 Sound Source Localization
6) Multi-Robot Formation Control
ROsOrin supports multi-robot communication and leader-follower coordination, enabling dynamic formation, path planning, and real-time obstacle avoidance. It supports line, column, and triangle formations, with multiple robots controlled simultaneously through one wireless controller.
Multi-Robot Navigation
Multi-Robot Formation
Multi-Robot Control
7) Deep Learning, Autonomous Driving
In the ROS system, ROsOrin has deployed the deep learning framework PyTorch, the open source image processing library OpenCV and the target detection algorithm YOLOv11 to help users who want to explore the field of autonomous driving technology easily enjoy Al autonomous driving.
Road Sign Detection
Through training the deep learning model library, ROsOrincan realize the autonomous driving function with Al vision.
Lane Keeping
ROsOrin is capable of recognizing the lanes on both sides to maintain safe distance between it and the lanes.
Autonomous Parking
Combined with deep learning algorithms to simulate realscenarios, side parking and warehousing can be achieved.
Turning Decision Making
According to the lanes, road signs and traffic lights, ROsOrin will estimate the traffic and decide whether to turn.
6. Gazebo Simulation
Hiwonder ROSOrin employs ROS framework and supports Gazebo simulation. Gazebo brings a fresh approach for you to control ROSOrin and verify the algorithm in simulated environment, which reduces experimental requirements and improves efficiency.
1) Body Simulation Control
Through robot simulation control, algorithm verification of mapping navigation can be carried out to improve the iteration speed of the algorithm and reduce the cost of trial and error.
2) URDF Model Display in RViz
Provide an accurate URDF model that can be visualized using the RViz tool to observe mapping and navigation performance, facilitating algorithm debugging and improvement.
View moreWhat’s Included
ROSOrin Starter Kit (with Jetson Nano 4GB Controller):
1* ROSOrin (assembled, LiDAR included)
1* Monocular camera
1* Wireless controller + Receiver
1* EVA ball (40mm)
1* Card reader
1* 12.6V 2A charger (DC 5.5*2.5)
1* WonderEcho Pro AI voice interaction box
1* Data cable (250mm)
1* Type-C cable (280mm)
1* Hex key
1* Accessary bag
1* User manual
Dimensions277x212x166mmSpecifications
Mecanum chassis version (Standard): Size: 277x212x166mm
Weight: 2.66kg
Ackerman chassis version (Standard): Size: 277x204x169mm
Weight: 2.15kg
Four-Wheel Differential Chassis Version (Standard): Size: 277x204x166mm
Weight: 2.26kg
Motor: 520 metal gear reduction motor
Encoder: High-precision AB quadrature encoder
Chassis material: Full-metal aluminum alloy chassis with anodized finish
ROS controller: Jetson Nano / Jetson Orin Nano / Jetson Orin NX / Raspberry Pi 5 board
Multi-function expansion board: STM32 ROS robot controller, Jetson multi-function expansion board
Control method: App control, wireless controller control, PC software control
Depth camera: Aurora 930 Pro 3D depth camera
LiDAR: MS200 TOF LiDAR
Battery: 1.1V 6000mAh 3C lithium battery
Audio/pickup: WonderEcho Pro Al voice interaction box / 6-mic array module
Operating system: Ubuntu 18.04 LTS + ROS Melodic / Ubuntu 22.04 / ROS2 Humble
Software: iOS / Android app
Communication method: WiFi / Ethernet
Programming tools: Python / C / C++ / JavaScript
Storage: 64G TF card (Jetson Nano, Raspberry Pi 5) 128G TF card (Jetson Orin Nano) / 128G SSD (Jetson Orin NX)
Servo model: LD-1501MG
Map/Props: AI sandbox map for autonomous driving, traffic lights, road signs
Tutorials: Comprehensive tutorials, ROS source code, system image, supporting software
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