The future of robots that our grandparents had dreamed of is coming. Despite major bottlenecks in our progress toward a world populated with autonomous robots, solutions are emerging daily. The cost bottleneck is being bypassed as technology and manufacturing evolve. Prices for humanoid robots are projected to hit $15,000 by 2050, making many cheaper than used cars and opening up access to millions of families. Teleoperation offers a scalable solution to the data bottleneck. Taken together, the industry has a much more practical near-term roadmap when it comes to higher-level autonomies. 

The Governance Gap

One bottleneck remains that cannot be simply solved by shifting capital or scaling data collection: trust. The same trust gap that exists in AI widens when robots operate in the real world. Concerns about job loss and privacy violations persist, as does algorithmic bias and discrimination. Amongst all of them, the common denominator is aligned, accountable human-robot interaction. 

Imagine a humanoid assistant sent to pick up a pizza with a $100 preloaded wallet. It returns with the order; however, the humanoid never paid for the pizza. Liability is ambiguous (owner, manufacturer, operator, or service provider) and current legal systems offer no clear answer. In order to bring autonomous robots into our everyday lives, we must create governance structures that can address when they fail to follow policy and that incentivize robot manufacturers and operators to prioritize safety and quality.

OpenMind’s founder, Jan Liphardt, points out that “our current rule sets (laws, constitutions, and charters) were built by people for people.” Identity, law, and finance are human-centric institutions, making it unfeasible to extend access to robots. Our identities are based on birth, our laws are crafted for humans, and our financial system relies on proof-of-humanhood. This quickly falls apart when a robot tries to open a US bank account without a Social Security number. Reform is necessary to enable human-robot interaction and to create trust, both in robots and in the people who manufacture and operate them. Thus, we need mechanisms to align incentives and behavior.

Humans already have a few systems for aligning incentives. Utilizing insurance models is one option where we file claims for robot misbehavior and receive payments in return, yet the process can be expensive, slow, and subjective. Insurers and courts have to be involved and insurers may decide they don’t want to take on this risk. Another option is regulatory oversight. Unfortunately, our governing bodies have long lagged by tech innovation. Finally, we could take on self-regulation, but only when backed by clear financial incentives. 

The Solution

To create a reliable governance structure for autonomous robots, we need to assign robots an identity, access to capital, and a legal code to abide by. Blockchains and smart contracts are ideal technology for creating digital governance and financial systems. Blockchains allow for universal digital identities that can be verified on-chain in order to drive trust in a machine economy. Smart contracts allow for executable outcomes to facilitate the whole system. Symbiotic’s Universal Staking and OpenMind’s FABRIC recognize the value of this technology in the development of the machine economy.

The Universal Staking framework presented by Symbiotic ensures that rules are enforced and penalizes stakeholders such as robot operators if they misbehave. Slashing conditions are defined by the network owner or coordinator. For this specific use case, on-chain verification is critical. Visibility is already easy on-chain, since everything can be verified immediately on the ledger. The issue is that robotics breaks this paradigm: most meaningful actions happen off-chain in the physical world, outside blockchain visibility. Without a bridge, machines cannot be rewarded or penalized without intermediaries. This is the role of OpenMind’s FABRIC: the oracle that brings real world data on-chain. To create trust without intermediaries, we need immutable verification.

The first step to verifiability is identity. On FABRIC, every connected device receives a cryptographic identity that anchors location, actions, and human ownership to specific robots. Each identity can then create cryptographic logs of proof-of-location, proof-of-work, and proof-of-custody which serve as attestation layers for rewards or punishments. As these logs grow in length, they will serve as a trust flywheel. Robots with longer periods of uptime and predictable behavior will receive increased cash flows rewarding quality and productivity. From there, Symbiotic takes over.

Taking this to the next level:

Think of FABRIC's current stage like a security camera system that records everything a robot claims it did, but you still have to trust that the robot isn't lying or that its sensors weren't compromised. As FABRIC matures, the network moves from "the robot says it did X" to "we can cryptographically prove the robot did X." This works through several key technologies. 

• Trusted Execution Environments create a secure vault inside the robot's processor where sensor data gets processed in a tamper-proof environment. Even if someone hacks the robot's main computer, they can't alter what the secure vault records. This means robots cannot produce corrupted claims. 
• Multi-party verification means robots don't verify themselves in isolation. Instead, nearby robots, IoT sensors, and infrastructure cross-check each other's claims, like having multiple independent witnesses to every action. This is similar to consensus mechanisms in blockchains. 
• Zero-Knowledge Proofs solve the privacy problem by letting a robot prove it did X without revealing the actual sensor logs or private information. This is important in scenarios such as healthcare where robots might handle patient data. Together, these technologies transform FABRIC from a system that requires human auditing into a foundation where robot actions become as provable as blockchain transactions.

Together, these primitives shift the system from detecting bad behavior after it happens to making bad behavior cryptographically impossible to hide or deny in the first place. Eventually, we have an autonomous machine economy enabled by machine-to-machine trust driven by cryptographic enforcement. FABRIC creates guardrails for the machine economy through on-chain reputation, access controls, and financial enforcement. All of which is anchored in device identity.

Through Symbiotic, smart contracts can integrate directly with FABRIC’s oracle and on-chain recordation layer. This allows Symbiotic vaults to operate not only on-chain collateral but also on verified off-chain data. By anchoring machine-generated events on-chain, Symbiotic enforces slashing and reward conditions in a fully trustless manner, extending staking guarantees into real-world machine interactions.

This integration sets the stage for the Machine Settlement Protocol, where agentic analysis of off-chain events determines when on-chain actions are triggered. By connecting Symbiotic’s universal staking framework with FABRIC’s oracle layer, settlement moves beyond pure financial transactions to include machine-to-machine trust and enforcement in the physical world.

Machine Settlement Protocol

Smart contracts aren’t really that smart, but they’re efficient. In order to be automated, slashing logic must be deterministic, meaning a defined threshold must be objectively crossed to trigger the event. For DeFi, deterministic logic works perfectly fine: if you’re trading with leverage and you fall below the collateral ratio your position is liquidated. Two issues arise when we try to replicate this system of execution in the real world: access to data and the subjectivity of real world events. 

The Machine Settlement Protocol (MSP) solves both of these issues by acting as an agentic oracle translating real world robot actions into verifiable triggers for smart contracts. Multimodal sensing (GPS, LIDAR, cameras) provides hard-to-spoof data that can be verified by agents to trigger on-chain actions and instant settlements. These agents can be humans, AI, or robots depending on the scenario. 

A Real World Example

Imagine an Amazon or FedEx employs a 3rd party robot delivery fleet to expand their overnight delivery capabilities. One robot malfunctions and fails to deliver a laptop, effectively robbing the recipient of their purchased item. Traditionally, an insurance claim would be filed and an investigation would ensue. This grueling process could take weeks as insurance companies fight over liability. In the worst case scenario, a post goes viral that undermines trust in the delivery fleet and costs Amazon. 

FABRIC streamlines the process of assigning liability and issuing compensation. The misbehavior is detected and cross-verified by nearby robots to proactively report the issue. The robot’s cryptographic logs show exact GPS location, package scanning, biometric confirmation, and handoff verification. MSP freezes the payment to the manufacturer while simple analysis of the log can determine who is at fault. After the robot is determined to be at fault, collateral from the manufacturer’s Symbiotic vault is slashed to allow Amazon to refund the customer. This collateral event is recorded on FABRIC and raises future staking premiums for the manufacturer.

The convergence of OpenMind's FABRIC verification layer and Symbiotic's universal staking creates the missing trust infrastructure for autonomous robotics. By putting financial capital behind robot performance, we transform deployment from a leap of faith into a calculated, market-driven decision.

The critical angle here is about making robots economically viable at scale. When operators stake real money on their robots' performance, and when verification comes from cryptographic proofs rather than human oversight, we create a system that drives continuous improvement while building public trust.

The path is clear: start with cryptographic logging to build accountability, evolve to verifiable proofs for precision enforcement, and ultimately enable a fully autonomous machine economy. OpenMind and Symbiotic are building this foundation today.

The future of robotics isn't just about better AI or cheaper hardware—it's about creating the economic infrastructure that lets humans and machines work together with confidence.

About Symbiotic

Symbiotic is a modular, permissionless staking framework designed to enable flexible and programmable economic coordination for onchain applications. It provides a generalized infrastructure where any protocol can create its own staking implementation with custom logic, roles, collateral types, and slashing conditions.

About OpenMind

OpenMind is building the universal operating system for intelligent machines. Its OM1 platform enables robots of all forms to perceive, adapt, and act in human environments. FABRIC, its decentralized coordination layer, creates secure machine identity and powers a global network where intelligent systems collaborate. Together, they lay the foundation for machines that can operate across any environment while maintaining security and coordination at scale.