As robotic automation has permeated the industrial space, many have been frustrated with its lack of scalability. Startups are stepping in to bring unique solutions to the constraints that have historically restricted automation to a small set of manufacturers and manufacturing processes.

The Problem: Lack of Scalable Programming

The cost of programming robots is higher than that of the hardware itself—typically three times more for a given installation. Robotics application development is more of a barrier than acquiring the robots themselves, both in terms of costs and skills to do it. 

Most robots run on outdated coding languages, which are often proprietary to each robot OEM, so there’s a limit on specialists who can program applications. 

How Startups Are Solving It

Innovative startups are working to avoid the outdated, unscalable programming requirements in a few ways.

No/Low Code Development

Startups like Ready Robotics, ArtiMinds, and drag&bot are working to bring no- and low-code development platforms to robots to work around the outdated programming language barrier and allow users to program via visual drag-and-drop editors. 

Demonstration Systems

Robot see, robot do. Southie Autonomy Works and Wandelbots use demonstration systems that “teach” the robot what to do. A human demonstrates the motions and the system translates those motions into the robot’s native code.

Pre-programmed Actions

Rapid Robotics has developed templates for dozens of common tasks that require only some configuration via an iPad app before being ready for use in production. 

The Problem: Stuck on Automation Instead of Autonomy

Automation and autonomy are very different capabilities. Automation is using robots to perform repetitive tasks in high-volume manufacturing contexts. Each robot’s scope of work is limited, and predictability is a must. 

An autonomous system, on the other hand, is one that can find a solution to unpredictable problems without external intervention.

How Startups Are Solving It

Improvements in the affordability and power of off-the-shelf sensing hardware have been major catalysts for advancements in autonomy. RIOS developed a proprietary haptic intelligence platform that facilitates objectives like the ability to handle delicate or deformable objects and to detect and correct slippage. Forcen developed a paper-thin force sensing film to support similar goals around robot dexterity.

Advancements in AI and machine learning technologies are a must for moving from automation to autonomy. RIOS and Vicarious use AI and ML program robotic autonomy in more complex environments. Micropsi Industries uses AI to power its demonstration systems, which allow humans to “show” a robot how to deal with variance.

The Problem: Lack of Mobility

Mobility involves the use of AMRs (autonomous mobile robots) to move materials between stages of the manufacturing process. Currently, most automation in manufacturing is stationary, completed by pivoting robotic arms that stay in one place on the line. 

The energy industry is using mobile, autonomous robotic vehicles to inspect assets and dangerous environments. And large ecommerce companies are using them for order fulfillment in warehouses. But manufacturing is still early in AMR adoption.

How Startups Are Solving It

Stationary robots fit into traditional belt production lines. But Arculus proposes a modular production layout where AMRs move materials through stations, scheduling routes in real time based on capacity and other considerations.

Other startups focused on AMRs in a manufacturing context include Arculus, OTTO Motors, R-Go Robotics, and Waypoint Robotics.

New startups are playing an important role in an old industry. As Optimus Prime would say, “Autobots, roll out.”