Palladyne™ IQ Delivers Closed-Loop Autonomy

Moving Beyond the Next-Generation of Robotic Automation Challenges:

Costly Implementation – Industrial robotics can take a long time to get up and running
Single-Tasking – Most industrial robots are highly programmed for one task only
Data and Power Consumption – Today’s deep learning AI approaches (e.g., LLM1 for generative AI) require vast amounts of training data and are power-hungry
Sensor Disruption – Often discrete and not optimized to work in unison with multiple sensors or to adapt and adjust for lost functionality of a single sensor

Closed-Loop Autonomy: Setting the Standard for Robotic Implementation and Operation

The Palladyne IQ robotic software platform is designed to enable machines to observe, learn, reason, and act like humans by:

Substantially accelerating speed of programming and training
Increasing agility to accommodate variability in task sets and use cases
Reducing the need for human intervention and oversight
Reducing cost of standing up and maintaining automation
Evolving from human-in-the-loop to human-on-the-loop operations
Eliminating the need for continuous cloud connectivity

“The key for us is enabling autonomy in an unstructured environment that can dynamically change. We focus on generalized autonomy, providing closed-loop functionality to adapt to tasks continuously.”

Dr. Denis Garagić

Palladyne AI CTO & co-founder

The Palladyne IQ Robotic Software Platform

The Palladyne AI approach to robotic automation differs from the rest. The advantages of the Palladyne IQ robotic software platform are highlighted by:

Purpose-Engineered to Perceive, Comprehend, and Conquer

Designed to tackle more dynamic and complicated tasks in arbitrary human environments
Delivering full-stack, closed-loop autonomy to enable adaptability to dynamic changes in environment or to a defined task – without human intervention or reprogramming
Taking advantage of probabilistic machine learning (ML) techniques to learn a task

Revolutionary AI Approach - Delivering Real-Time Learning & Reasoning

Dynamic model inference methods require less training data – helps robots learn with fewer demonstrations
Domain-specific language models provide computational efficiencies for specific environments or workflows
Language-to-motion instructions ideal for edge computing/robotics applications – not requiring persistent connectivity to the cloud

Hardware Agnostic and Ready for Industry-Wide Adoption

Addresses robotic-specific challenges beyond integration
Enabling on-device computing to help lower the total cost of ownership (TCO) and avoid recurring cloud services costs
Designed for stationary and mobile robotic platforms for a broad range of applications:
- Industrial robots and cobots
- Unmanned aerial vehicles
- Unmanned ground vehicles and humanoids

Observation: Perceiving the World

The ability for robotic systems to comprehend their surroundings is the foundation upon which our platform builds its remarkable capabilities.

Learning: Accelerated Adaptation

The learning process is expedited, with robots typically acquiring a new task in just one to five human-controlled demonstrations. This efficient learning process ensures your operations remain agile and responsive to ever-changing demands.

Reasoning: Human-Like Logic

Robots powered by the Palladyne AI software platform are able to reason similarly to human logic when faced with unexpected events. The stored Task Library serves as a starting point, allowing the robot to adjust to circumstances in real-time, ensuring seamless operation and uninterrupted productivity.

Action: Intelligent Execution

Applying human-like logic, robots adapt their task model in real-time to translate observations into precise control messages, ensuring safe and controlled completion of tasks without the need to halt production for reprogramming after disruptions. Your operations will run smoothly, even in the face of unexpected challenges.

Talk to Palladyne AI

By enabling autonomy, reducing programming complexity, and enhancing efficiency, we are paving the way for a future where machines can excel in tasks that were once considered beyond their reach.