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Hiwonder LanderPi: Raspberry Pi AI Robot Car with Vision Arm, ROS2 & ChatGPT Support

Price range: $398.70 through $890.80

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Features & Compatibility

[Raspberry Pi 5 & ROS2 Robot Car]

LanderPi is powered by Raspberry Pi 5, compatible with ROS2, and programmed in Python, making it an ideal platform for AI robot development.

[Multiple Chassis Configurations]
LanderPi robot supports Mecanum-wheel, Ackermann chassis, and tank chassis, allowing flexibility for various applications and meeting diverse user needs
[High-Performance Hardware]
Equipped with DC gear encoder motors, TOF lidar, 3D depth camera, 6DOF Robotic Arm, and other advanced components to ensure optimal performance and efficiency
[AI Advanced AI Capabilities]
LanderPi Raspberry Pi car supports SLAM mapping, path planning, multi-robot coordination, vision recognition, target tracking, and more, covering a wide range of AI applications.
[Autonomous Driving with Deep Learning]
Utilizes the YOLOv8 model training to enable road sign and traffic light recognition, along with other autonomous driving features, helping users explore and develop autonomous driving technologies.
[Empowered by Large AI Model, Human-Robot Interaction Redefined]

LanderPi deploys multimodal models with ChatGPT at its core, integrating 3D vision robotic arm and AI voice interaction box. This synergy enhances its perception, reasoning, and actuation capabilities, enabling advanced embodied AI applications and delivering natural, context-aware human-robot interaction.

Product Description
LanderPi robot car is a composite ROS educational robot developed by Hiwonder. It supports three motion chassis: Mecanum wheel, Ackerman, and Tank chassis. It is equipped with Raspberry Pi, large-torque encoding motors, and 6DOF robotic arm. High-performance hardware configurations such as lidar, 3D depth camera, and AI voice interaction box can realize robot motion control, mapping navigation, path planning, tracking and obstacle avoidance, autonomous driving, 3D grabbing, navigation and handling, somatosensory Interaction, AI voice interaction, group control formation, and other applications.
LanderPi also deploys a Multimodal Large AI Model to support more advanced embodied AI applications. To help you unlock its full potential, open-source code and learning resources are provided to inspire and support your AI projects.

6DOF Robot Arm, Intelligent Bus Servo

Equipped with a 6DOF robot arm and high-torque bus servos, LanderPi achieves superior performance and longer operating endurance.

Lidar SLAM Mapping Navigation

LanderPi robot car is equipped with lidar, which can realize SLAM mapping and navigation, and supports path planning, fixed-point navigation and dynamic obstacle avoldance.

Depth Vision First-Person View

With a 3D depth camera mounted at the end of its 6DOF robotic arm, LanderPi provides first-person visual intelligence for precise object recognition, tracking, and grasping.

WonderEcho Pro AI Voice Box

LanderPi Advanced Kit comes with a WonderEcho Pro AI voice box that delivers excellent noise reduction and clear audio capture. It supports advanced features such as speech recognition, voice broadcast, and voice control.

Dual-Controller Design for Efficient Collaboration

Function List

Integration of Large AI Model with SLAM Mapping & Navigation

Hiwonder LanderPi car 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 robot’s intelligence, adaptability, and overall user experience, making it better suited to meet real-world needs.

Semantic Understanding

LanderPi robot car leverages a large language model to accurately interpret and analyze user voice commands, enabling a deeper understanding of natural language intent.

Intelligent Navigation

LanderPi Raspberry Pi robot 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.