Open Humanoid — Engineering the Autonomous Robot

Research Series

DOI 10.5281/zenodo.18946974

Open Humanoid: An Open-Source Engineering Series for Autonomous Bipedal Robots

Oleh Ivchenko¹

¹ Odesa National Polytechnic University (ONPU)

Type: Engineering Research Series
Status: Ongoing · 8 of 20 articles published
Tool: Humanoid Simulation → GitHub

8 Articles · 20 Planned Total · 2025–2026 · Article 8/20

Abstract

Autonomous bipedal humanoid robots remain fundamentally closed systems: proprietary designs, protected specifications, and restricted development. This research series opens that paradigm by publishing a complete, reproducible engineering methodology for designing and building an autonomous humanoid robot from first principles. Across 20 planned articles, the series covers locomotion, actuation, structural materials, power systems, perception, computer vision, sensor fusion, manipulation, speech interfaces, navigation, control architecture, and real-time safety systems. Every design decision, trade-off, and failure mode is documented as it happens. The work anchors to a version-controlled specification (MASTER_SCHEMA.md) that serves as the single source of truth, enabling reproducibility and collaborative extension across research groups.

Idea and Motivation

Humanoid robotics research is concentrated in a small number of well-funded institutions and commercial ventures, each with proprietary designs and restricted access to engineering details. The result is slow innovation, high costs, and fragmented knowledge. There is no canonical reference design, no shared methodology, and no transparent pathway for researchers, students, and practitioners to contribute.

This series begins with a provocative premise: autonomous humanoid robots can be designed, specified, and built in public — with transparent trade-offs, documented constraints, and engineering decisions available for scrutiny and extension. The research question is not whether we can build a humanoid; the robotics literature is clear that we can. The question is: what happens to the pace and accessibility of humanoid robotics research if we build one entirely in the open?

Goal

The series aims to build a complete, peer-reviewed engineering methodology for autonomous humanoid robots that is reproducible, extensible, and publicly accessible. This means not just publishing final designs but documenting the iterative process: failed approaches, computational constraints, mechanical trade-offs, and the reasoning behind each decision. The goal is a self-contained research corpus that any research group—from university labs to hobbyist makers—can use as a foundation for their own humanoid systems.

By anchoring the work to a version-controlled specification (MASTER_SCHEMA.md), the series ensures that every article references a clear, unambiguous system design. The specification is simultaneously human-readable and machine-parseable, enabling both engineering understanding and computational reproducibility.

Scope

The research spans 20 articles across the complete engineering stack of an autonomous bipedal humanoid robot. The series progresses from foundational concepts (specification and locomotion) through sensing, perception, and control, to advanced topics including manipulation, human-robot interaction, and system integration. Below is the complete 20-article roadmap with current publication status:

Table 1. Open Humanoid 20-Article Research Roadmap
Article	Title	Status
1	Introduction & Why Open Source	Published
2	Full Engineering Specification (MASTER_SCHEMA.md)	Published
3	Bipedal Locomotion: Gait, Balance, and Fall Recovery	Published
4	Actuation & Motors: Torque Budgets and Degrees of Freedom	Published
5	Structural Materials: Design, Stress Analysis, and Manufacturing	Published
6	Power Systems: Battery Chemistry, Autonomy Budget, and Heat Management	Published
7	Sensing & Perception: IMU, Force-Torque, Camera Integration, Sensor Fusion	Published
8	Computer Vision & SLAM: Depth Perception, Object Detection, Navigation	Published
9	Hand & Manipulation: Dexterous Fingers, Grasp Planning, and Force Control	Planned
10	Speech Interface: Voice Recognition, Synthesis, and Intent Understanding	Planned
11	Navigation: Path Planning, Obstacle Avoidance, and Semantic Mapping	Planned
12	Force Control: Impedance, Compliance, and Contact Dynamics	Planned
13	Safety Architecture: Fault Detection, Monitoring, and Emergency Stop	Planned
14	Real-Time Control: Operating Systems, Scheduling, and Determinism	Planned
15	Multi-Robot Communication: Coordination, Messaging, and Distributed Control	Planned
16	Simulation: Physics Engines, Digital Twins, and Validation	Planned
17	System Integration: Assembly, Commissioning, and First Motion	Planned
18	Prototype Manufacturing: CAD-to-Hardware, Tolerancing, and QA	Planned
19	Benchmarking: Metrics, Testing Protocols, and Success Criteria	Planned
20	Full System Validation: Static and Dynamic Balance, Autonomous Operation	Planned

Each article builds incrementally on the specification and preceding work. Early articles establish foundational constraints (locomotion physics, power budgets, material properties). Middle articles address perception and control (sensing, computer vision, real-time execution). Later articles tackle integration challenges (manipulation, communication, simulation, manufacturing, and system-level validation).

Focus

The primary technical focus is on complete systems engineering from first principles, not isolated component optimization. Every subsystem (mechanical, electrical, computational) is designed with full awareness of constraints imposed by other subsystems. The series emphasizes the trade-off space: why certain designs were selected, why others were rejected, and what was sacrificed to achieve a working integrated system.

Special emphasis is placed on:

Reproducibility: Every design decision is anchored to the version-controlled MASTER_SCHEMA.md specification. No hand-waving; every claim is backed by measurable parameters.
Open-source methodology: The entire project is developed in public on GitHub, with transparent issue tracking, design evolution, and community contributions.
Resource constraints: The robot is designed to be buildable by a small research team on a reasonable budget, not with unlimited aerospace-grade resources.
Real failure modes: Documenting not only what works but what doesn’t—failed motor selections, structural weak points, control instabilities—creates valuable negative knowledge.

Limitations

Single-point designDescribes one specific humanoid architecture. Findings do not generalize to all bipedal robots or all actuation paradigms.

Prototype-stage systemArticles document design and early simulation/testing. No large-scale manufacturing or clinical deployment data yet available.

Academic environmentDevelopment occurs at a university research lab. Commercial manufacturing, regulatory approval, and real-world deployment introduce additional constraints not yet addressed.

Simulation-heavy early stageArticles 1–8 rely primarily on simulation and design analysis. Physical validation comes in later articles (17–20).

Scientific Value

The series makes three contributions to the field. First, it provides a transparent, reproducible reference design for autonomous humanoid robots—a gap in the existing literature, which is dominated by proprietary systems with restricted design documentation. Second, it demonstrates that open-source methodology can be applied to complex systems engineering, creating a model for how future robotics research can be conducted in public. Third, it establishes a standardised specification format (MASTER_SCHEMA.md) that enables computational validation, simulation, and collaborative extension across distributed research teams.

The published articles and GitHub repository serve as both research output and ongoing research tool: each article advances understanding of a specific subsystem while simultaneously contributing to a working integrated system. Future work can reference and build upon this foundation without repeating foundational design work.

Resources

Status

Ongoing. 8 of 20 articles published as of March 2026. Articles 1–8 complete, covering specification through computer vision and SLAM. Articles 9–20 are planned and in active development. New articles are published on a rolling basis as research milestones are achieved. The project roadmap and current progress are tracked in the GitHub repository and updated with each release.

Contribution Opportunities

Researchers and engineers wishing to contribute to this work are encouraged to engage with the following opportunities:

Experimental validation: Replicate the simulated designs in physical hardware. Build your own instance of the robot using the MASTER_SCHEMA.md specification and document deviations and improvements.
Subsystem optimization: Propose improvements to specific components (motors, structural materials, sensor configurations) with performance analysis and trade-off documentation.
Extended specifications: Add new modalities to the MASTER_SCHEMA.md—e.g., different sensor suites, alternative actuators, or scaled variants.
Distributed implementations: Develop alternative implementations of the control software, perception pipelines, or simulation environments that interoperate with the core specification.
Cross-system research: Test methodologies and findings against other open humanoid platforms to evaluate generalisability and best practices.