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Robotics+AI (Part 2) Development: Advanced task sensing, learning, adapting

INTRINSIC dual robots

INTRINSIC demonstrating two robots trained with AI to coordinate

This is Part 2 of 4 in a series on Robotics+AI :
recent developments, and the surprising realities we grapple with.

INTRINSIC (an Alphabet company) software and tools to make industrial robots easier to use, less costly, and more flexible, enabling new products, businesses and services.

Why needed  

The cost and complexity to program robots for industrial applications, particularly in the complex area of sensing and adapting to the environment, with time running into hundreds of hours.

What it offers

INTRINSIC software and AI tools significantly simplifies the development of industrial robots’ ability to sense, learn and automatically make adjustments while on task, so they can be applied in a wider range of settings and applications.

Sensor data from the robot’s environment can be practicably used to “sense, learn from, and quickly adapt to the real world.”

INTRINSIC technique automation areas include: automated perception; deep learning; reinforcement learning; motion planning and simulation; force control; simulation.

Hard-coding that has taken 100’s of hours, can now reduce to 2 hours.

Why significant

Dexterous and delicate tasks, like inserting plugs or moving cords, have eluded robotics because they lack the sensors or software needed to understand their physical surroundings.

Industrial-robot development is key to advanced manufacturing,  especially in the face of decreasing labor availability ( 2.3Mn short by 2030).

With the Intrinsic software and tools, developers can reimagine industrial-robots. We can take advantage of the declining cost of industrial robot hardware, and the availability of lower-cost sensors for perception and tactile skills.

What still keeps us awake at night

How does a robot recognize and keep safe a human worker straying into its workspace?

Human Safe Zones and distancing
  • Industrial robots operate in what are essentially controlled and constant environments.  The difficulties with task-related variables are challenging enough, let alone truly grasp and respond to what is happening around them, outside of their learning sets. 
  • The current state of the art does not give robots the awareness and intelligence to work with humans, who must observe specified safety zones.
  • Guidelines and regulations are still emerging along with the robots themselves. The US NIOSH is developing standards for industrial robots specifying “guarded areas” to maintain safe distance from humans. For Europe, the THOMAS.EU project offers guidelines.
  • NIOSH categorises robots as: (1) industrial; (2) professional and personal service; (3) collaborative robots. “Collaborative” involves working alongside humans. (See NIOSH)

What can we learn from autonomous-vehicle development issues?

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