Clearpath Dingo

Name: Clearpath Dingo
Brand: Clearpath Robotics

Compact indoor robotics research and development platform

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The Clearpath Dingo is a compact, lightweight indoor mobile robot platform designed for research, development, and education. Featuring omnidirectional mobility and a small footprint, it excels in confined spaces and laboratory environments. The platform is ROS-native and highly customizable, making it ideal for academic institutions, research labs, and developers working on navigation, manipulation, and multi-robot systems.

Released: 2019

Overview

The Clearpath Dingo represents a new generation of compact mobile robotics platforms designed specifically for indoor research and development environments. With its small footprint measuring just 482mm square and weighing only 14.5kg, the Dingo is engineered to operate effectively in constrained laboratory spaces, office environments, and academic facilities where larger platforms would be impractical.

Built on Clearpath Robotics' proven expertise in autonomous mobile robots, the Dingo features omnidirectional mobility through its mecanum wheel configuration, enabling precise maneuvering in tight spaces. The platform is fully ROS-integrated out of the box, providing researchers and developers with immediate access to the extensive ROS ecosystem and toolchain.

Designed with modularity and extensibility in mind, the Dingo serves as an ideal foundation for projects involving autonomous navigation, human-robot interaction, multi-robot coordination, and manipulation research when paired with lightweight robotic arms. Its indoor-optimized design and accessible price point make it particularly attractive to academic institutions and small research teams.

Key Features

Omnidirectional mobility: Mecanum wheels enable holonomic motion for precise positioning and maneuvering in confined spaces
Compact footprint: 482mm x 482mm x 254mm dimensions ideal for indoor laboratories and office environments
High payload capacity: Supports up to 20kg for sensors, manipulators, and custom payloads despite its compact size
ROS-native integration: Fully compatible with ROS/ROS2 with pre-configured drivers and simulation support
Extended runtime: 4-hour battery life supports prolonged research sessions and autonomous operations
Modular design: Standardized mounting points and power distribution for easy integration of sensors and accessories
Indoor-optimized: Designed specifically for smooth indoor surfaces with quiet operation suitable for shared workspaces

Applications

The Clearpath Dingo is primarily utilized in academic research institutions, corporate R&D laboratories, and educational settings where indoor mobile robotics research is conducted. Its compact size makes it ideal for multi-robot system research, swarm robotics experiments, and human-robot interaction studies in realistic indoor environments. Universities leverage the Dingo for teaching robotics fundamentals, autonomous navigation algorithms, and sensor fusion techniques.

Industrial research teams use the Dingo platform for prototyping warehouse automation concepts, testing collaborative robot behaviors, and developing indoor positioning systems. When equipped with manipulators, the Dingo serves as a mobile manipulation platform for research in assistive robotics, laboratory automation, and service robotics applications in retail and hospitality environments.

Technical Highlights

The Dingo's mecanum wheel drivetrain represents a key technical achievement, providing true omnidirectional movement that allows the robot to translate in any direction and rotate simultaneously without repositioning. This holonomic capability is essential for research in advanced motion planning and control algorithms. The platform's lightweight aluminum chassis incorporates optimized weight distribution to maximize the 20kg payload capacity while maintaining stability.

Clearpath has engineered the Dingo with a robust electrical architecture featuring multiple power rails and extensive I/O options, enabling seamless integration of diverse sensor suites including lidars, depth cameras, and IMUs. The platform's native ROS integration includes pre-built URDF models, Gazebo simulation support, and fully documented APIs, significantly reducing development time for researchers and allowing immediate focus on algorithm development rather than low-level hardware integration.