Introducing Robora

Welcome to Robora's Official Documentation and Resources.

Robora's documentation, including this Gitbook, is regularly updated with the latest information. Always refer to the most recent version for accurate details.

Robora team members will never reach out to you first. Please contact us if you have any questions or concerns.

Community: Join our Telegram & Twitter to get the latest and most important announcements, updates and interact with the team and community members.

The robotics industry faces significant hurdles:

Fragmented data sources (e.g., incompatible sensor logs from different manufacturers). This leads to duplicated efforts, high integration costs, and slow progress, preventing broader adoption and making it difficult to build scalable, unified systems;
Limited Decentralized Real-World Data Collection: Real-world robotics data is scarce and centralized, often locked in proprietary datasets or requiring expensive collection methods. Human-labeled insights (e.g., via questionnaires on task outcomes) are underrepresented, resulting in models that lack nuanced understanding and generalization, stifling AI training.
Inefficiencies in Local Execution and Scaling: Robots require low-latency local execution for dynamic tasks, but scaling to fleets introduces centralization risks, high costs, and coordination challenges. Without seamless support for distributed resources, robotics systems struggle with reliability in varying environments, limiting their use in real-time applications like navigation or assembly.
Lack of Modular Robot Building Tools: Building custom robots is complex and inaccessible, with limited tools for modular hardware assembly integrated with AI. This results in rigid designs that don't easily incorporate embedded intelligence, hindering physical IoT/robotics control and slowing innovation for diverse use cases
Absence of Economic Incentives for Collaboration: The robotics ecosystem lacks mechanisms to reward contributions, such as bidding marketplaces for hardware, software, or data packages. Without gamified elements for training AI components (e.g., Synths), users have little motivation to share resources or data, perpetuating silos and underutilizing collective potential.

Robora addresses these challenges by building an open, blockchain-based coordination layer that connects developers, IoT users, data providers, and robotics companies.

How do we solve these issues?

Robora's goals in simple terms are the following:

Unify Robotics Data and Software: Create a platform that standardizes data formats and software stacks for diverse robots, reducing silos and enabling broader adoption.
Enable Decentralized Data Collection: Allow users to contribute real-world data via questionnaires (providing human-labeled insights) and uploads, rewarded with $RBR tokens.
Support Local Execution with Scaling: Run Synths, embedded with a fine-tuned VLA-model, (semi) locally on robots for low-latency tasks, with coordination for fleet scaling.
Facilitate Modular Robot Building: Offer a 3D builder for assembling hardware with embedded Synths, supporting physical IoT/robotics control.
Drive Economic Value: Build a bidding marketplace for robotics packages (hardware, software, data), with gamified elements for Synth training.

At the heart is the Grid Framework, which orchestrates workflows (powered by the Nexus-Hub), and Synths, embedded executors that make robots intelligent and autonomous.

This whitepaper explains all components in detail, from architecture to workflows, demonstrating how Robora achieves its vision of accessible, scalable robotics AI.

We've put together some helpful guides for you to get setup with our product quickly and easily.