Asimov Open SDK, Humanoid Robot Competition Shifts to Developer Ecosystem

On October 12, Menlo Research announced the release of its humanoid robot Asimov 1Python SDK, along with the opening of the robot control software Asimov Edge. According to a report by the robotics industry media Humanoids Daily, the newly released SDK supports walking commands, joint control, robot status reading, and the invocation of cameras, microphones, and speakers. Developers can make the robot perform actions through Python programs, and also integrate visual, audio, and autonomous control programs with existing hardware. The SDK uses the Apache 2.0 license, and the related code and development documentation have been made public; however, as of the time of the report's publication, the media has not yet found the publicly available source code for Asimov Edge, so the extent of the openness of the control layer still needs to be further verified.

The industry significance of this news lies in the fact that the competitive boundaries of the humanoid robot industry are extending toward software tools and developer experiences. In the past, the industry focused on whether robots could walk stably, complete grasping, and whether key components could be cost-reduced; as robots gradually gain programmable capabilities, another question has begun to become important: can external developers use lower costs to integrate robots into their own applications, algorithms, and business processes?

Smartphones provide a valuable reference. Hardware performance determines the basic capabilities of a product, while the operating system, development tools, and application distribution mechanisms determine whether developers can continuously create value. Robots also have similar opportunities, but the two cannot be simply compared. Mobile applications typically run in relatively standardized computing environments, while physical robots will face issues such as joint control, motion stability, sensor errors, physical collisions, and device safety.

Menlo Research has opened up its SDK interface, allowing researchers, engineers, and application developers to more easily access real hardware and save the effort of repeatedly building low-level control tools. For a robotics company that positions open design and programmable capabilities as its selling points, this step has the potential to expand the user base, and the subsequent business opportunities such as tool chains, development services, and application collaborations will also have room for development.

The robotics industry is beginning to catch up on software: hardware capabilities need to be converted into callable development interfaces

The advantage of Asimov 1 is that Menlo Research aims to integrate mechanical design, motion control, and application development within a relatively open framework. The company's official website positions it as a humanoid robot for full-body control and motion research, offering development directions such as customizable hardware, simulation, and real robot testing. Official data indicates that Asimov 1 is approximately 1.2 meters tall, weighs about 35 kilograms, and is equipped with 25 drive joints; motion control is handled by Radxa CM5, while media processing and network connectivity are handled by Raspberry Pi 5.

The industry changes behind these configurations are that robot development is moving from single hardware debugging toward layered software engineering. The lower layer is responsible for joints and motion control, the middle layer handles state feedback, communication, and control permissions, and the upper layer runs visual recognition, task planning, and applications. A layered architecture helps different teams collaborate around their respective strengths, and also reduces the cost of redeveloping an entire control system for each application project.

The Menlo SDK released this time is precisely packaging part of the lower-level capabilities into interfaces that developers can directly use. According to the official documentation, developers can call standing, balancing, walking, and joint control functions through Python, and can also read robot status and access audiovisual data. The SDK supports local UDP communication, as well as network connectivity and remote operation through LiveKit; the project also provides sample programs, interface descriptions, and documentation for programming agents, making it convenient for developers to start building applications from existing code.

The value of such tools is not hard to understand. For robotics research teams, development time is often spent on device access, control interface adaptation, and repeated debugging; for visual algorithm companies, once an algorithm identifies an object, it still needs a stable interface to convert the recognition results into robot actions. If an SDK can reduce these repetitive tasks, it has the potential to shorten the cycle from algorithm validation to physical device testing, allowing more teams to participate in application development.

However, the significance of opening interfaces still depends on actual usage. Walking, reading joint status, and controlling the upper limbs are basic capabilities, and there is still a long way to go before robots can independently complete complex tasks in factories or homes. Robots need to handle perception, planning, action execution, and exception recovery simultaneously, and a single interface cannot replace a complete autonomous system. For Menlo Research, whether the SDK can attract developers to continuously submit code, share projects, and form reusable solutions on real devices is more indicative than the amount of attention it receives on the day of release.

Opening the SDK is just the beginning: the barriers of the developer ecosystem lie beyond the interfaces

The robot industry often discusses open ecosystems, but the level of openness varies. Publishing mechanical design files can help developers understand the hardware and make modifications; publishing motion training code allows researchers to study strategy training methods; publishing an SDK further reduces the threshold for invoking robot capabilities. Menlo Research had previously published the motion strategy training code for Asimov 1, and this release of an SDK makes it easier for external developers to connect algorithms with real robots.

The more challenging work ahead is to ensure that programs written by different developers can run stably and remain compatible after software updates. Unlike regular software, which can be simply restarted when issues occur, motion commands may lead to real physical consequences. Communication delays, state reading errors, or control authority conflicts can all affect device operation. Therefore, the interface design, exception handling, version management, and security mechanisms of the SDK will ultimately determine whether developers are willing to use it for long-term projects.

Asimov Edge is particularly worth tracking. According to a report by Humanoids Daily, this control layer is responsible for coordinating control commands from different sources such as SDK applications and manual remote operations, and after processing priority, forwards the commands to firmware. This mechanism determines how the system decides who can control the device when multiple applications are connected to the robot. The media reported on October 12 that the Edge's open source code had not yet been released, so judgments regarding its open source progress should be based on the actual repository and license, not solely on the company's release statement to conclude that the control layer has been fully opened.

This is also one of the most important differences between the open ecosystem of robots and that of smartphones. Smartphone developers mainly face issues such as operating system permissions, hardware adaptation, and app review, while robot developers also need to address the physical device's security responsibilities, control authority management, and the uncertainty of real-world environments. The higher the level of openness, the more critical it is to have clear security boundaries, comprehensive testing tools, and traceable error handling mechanisms. The official documentation also clearly warns that the SDK is not an emergency stop device, and physical devices still require independent emergency stop measures and operational safety procedures.

Therefore, evaluating Asimov's developer ecosystem cannot only focus on whether there is code on GitHub, but also should observe whether the documentation can help newcomers complete their first development, whether the simulation environment can shorten the time required for real device debugging, whether hardware and software upgrades maintain compatibility, and whether external teams can migrate their programs to different devices or application scenarios. For enterprise customers, these details determine whether the robot is a device that requires a dedicated team for maintenance or a development platform that can be integrated into existing research and development processes.

From development tools to commercialization: Menlo Research needs to prove that the ecosystem can create demand

Menlo Research's open approach provides the company with potential developmental space beyond simple hardware sales. Developers studying motion control, visual perception, and remote operation through the SDK can bring more test scenarios and technical feedback to the platform; these feedbacks have the potential to help the company refine interfaces, improve products, and expand collaborations with research institutions, robot startups, and industrial clients.

The company's official website currently provides product introductions, development documentation, and sales contact entry points for Asimov 1, and also showcases digital twins development experience directions. Digital twins allow developers to test code without the involvement of a physical robot. If such tools can form a stable connection with real hardware, they have the potential to reduce early development dependence on physical devices, allowing potential customers to validate technical solutions before purchasing.

Judging the company's business model requires distinguishing between already established product capabilities and still unproven revenue opportunities. While open SDKs can expand the potential user base, publishing code itself cannot directly prove improvements in hardware sales, software revenue, or customer retention. More attention in the future should be given to whether developers can be converted into hardware buyers, enterprise project clients, and long-term partners, as well as whether external developers are willing to continuously build applications around Asimov.

If an open toolchain can form a stable usage, the company will have the opportunity to expand its business around robot hardware, development support, customized projects, and related services. If application development gradually solidifies into reusable software assets, the company may also reduce the cost of developing each project from scratch. However, these are all commercial directions that need to be validated by subsequent operational data, and at this stage, they should not be regarded as already formed revenue structures.

Industry competition will also affect the speed of realizing this path. Large robot companies have resources in hardware development, funding, and application scenarios, enabling them to push products to market through internal teams; open platforms, on the other hand, rely more on the willingness of external developers to participate and the maturity of the toolchain itself. The actual question Menlo Research needs to answer is: why would developers choose As, rather than other robot platforms: whether the interface is easy to use, whether the equipment is easy to maintain, whether the transition between simulation and reality is smooth, and whether the development results can truly be converted into stable robot behaviors.

For potential partners, it is more worthwhile to figure out two questions than to look at a single product demonstration: which capabilities related to robot control, simulation testing, visual and audio algorithms, developer tools can be quickly validated through open interfaces, and which still require the company to provide underlying support. The cooperation opportunities ultimately depend on the degree of technical compatibility, project delivery capabilities, and real demand; the open label itself does not mean much.

Conclusion | The value of a robot platform ultimately needs to be proven by developers' continuous use

The fact that Asimov has opened its Python SDK is worth following, as its root lies in directly handing over the motion, status, and media capabilities of real robots to external developers, thereby shifting the competition of robot platforms from hardware parameters to development experience.

Of course, an ecosystem needs time to grow. Code release is just the beginning; interface stability, documentation quality, simulation tools, hardware compatibility, and the number of real projects will gradually determine whether the platform can gain continuous use. For Menlo Research, the truly convincing signals in the future will be whether external developers start delivering reusable applications, whether enterprise customers are willing to use the platform for actual projects, and whether the open toolchain can continuously reduce R&D and deployment costs.

The technology and business models of humanoid robots are currently in a phase of joint exploration. Companies with reliable hardware have the opportunity to secure the first batch of users; platforms that can continuously enable developers to create new uses will have the opportunity to expand the product's application boundaries. Asimov has already taken a step in this direction; next, it will depend on developer participation, application results, and customer demand to bring the value of the open platform from technical interfaces all the way to commercial realization.