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Elevating Robots 

Digital Cortex Augmentation

Our IQ-130 is a cutting-edge add-on intelligence solution that elevates any robot's capabilities to become an intelligent and adaptable machine. By integrating IQ-130, a robot's reasoning, planning, acting, decision-making, and teaming abilities are significantly enhanced, enabling it to operate in complex and dynamic environments.

Whether attached directly to a robot or remotely implemented, IQ-130 empowers robots to work seamlessly with humans and other robots using a common domain-specific ontology, allowing for effective communication and collaboration. With IQ-130, robots are able to navigate unfamiliar terrain and operate in unstructured environments with ease, ensuring optimal performance in a wide range of scenarios

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IQ-130 Features 

- Human-Machine & Machine-Machine interaction

- Support complex tasks 

- Support amorphic missions

- Support amorphic teaming missions

- Support first-time-seen environments 

- Embedded low-fidelity world models  

- Embedded domain-specific KG

- Ontology based reasoning engine

- Abstract low-latency planner 

- Input: semantic I/F (objects)

- Output: High level actions (actuators)

Use Cases

IQ-130 was designed as an add-on intelligence solution for service robots, industrial robots, warehouse robots, home robots and any autonomous platform which faces unstructured, first-time-seen environment.    

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Our IQ-130 solution offers several advantages over rule-based systems.

- Flexibility: IQ-130 is more flexible because it can handle complex and diverse tasks.

IQ-130 handles tasks with multiple goals, conditions, and subtasks, whereas rule-based systems are limited to tasks with a fixed sequence of decisions.

- Reusability: IQ-130 can reuse the same hierarchical structure for different tasks. In contrast, rule-based systems require a new decision tree to be created for each new task.

- Robustness: IQ-130 is more robust than rule-based systems because it can handle incomplete or missing information. Rule-based systems require all information to be available at each decision point.

- Scalability: IQ-130 can scale better than rule-based systems because it use a hierarchical structure that can be decomposed into smaller, manageable tasks. In contrast, rule-based systems can quickly become unwieldy and difficult to manage as the number of decisions and paths increase.

- Human-Like Reasoning: IQ-130 can model human-like reasoning, which makes it easier for people to understand and interact with them. Rule-based systems are limited to a fixed set of rules and cannot adapt to new situations or unexpected events.

- Modularity: IQ-130 can be modular, meaning that different parts of the planning process can be modified or replaced without affecting other parts. This makes it easier to update or change specific components of the planning process without having to overhaul the entire system.

- Goal-Directedness: IQ-130 is goal-directed, meaning that they focus on achieving specific goals rather than following a fixed sequence of decisions. This makes it more efficient at finding solutions to complex problems.

- Re-planning: IQ-130 can handle changes in the environment or new goals by re-planning and adjusting its hierarchy of tasks. This makes it more adaptable to changing circumstances and requirements.

- Learning: IQ-130 can learn from experience and improve its performance over time. This is particularly useful in dynamic and uncertain environments where the planner must continually adapt to new information.

- Domain-Specificity: IQ-130 can be designed to be domain-specific, meaning that it can be tailored to specific industries or applications. This makes it more efficient and effective in those domains.

- Plan Execution: IQ-130 can handle the execution of plans, not just the planning process itself. This means that it can monitor the environment and adjust the plan in real-time based on feedback from sensors or other sources.

- Multi-Agent Systems: IQ-130 can be used to coordinate the actions of multiple agents in a multi-agent system. This is particularly useful in applications such as robotics, where multiple agents must work together to achieve a common goal.

- Interpretability: IQ-130 is more interpretable than rule-based systems, meaning that it is easier to understand how the planner arrived at a particular solution. This can be useful for debugging and improving the planner's performance.

- Uncertainty Handling: IQ-130 can handle uncertainty and ambiguity in the planning process. This is important in applications where the environment is uncertain, or the planner has incomplete information.

- Complexity Handling: IQ-130 can handle complex tasks that require reasoning at multiple levels of abstraction. This makes it well-suited for applications such as scheduling or logistics, where there are many interrelated tasks to be managed.

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