Robots Need to Master Autonomous Tool Manipulation to Expand their Roles in Manufacturing

Many psychologists believe that humans’ ability to use complex tools makes them different from animals. Tools enable humans to overcome limitations in speed, reach, and force in manipulating or making value-added changes to objects. Using tools provides a way for humans to manipulate objects indirectly – humans manipulate tools, and tools manipulate objects. This mode of operation amplifies human abilities. All modern manufacturing processes use tools to make objects or modify the surfaces of the objects created by another method.      

Using hammers and screwdrivers is relatively simple. Many surface treatment processes require complex tool manipulation: sanding, polishing, buffing, trimming, coating, spraying, and blasting. Four factors lead to complexity:  

  • Tools must perform complex motions to work on objects with difficult-to-reach features and avoid damage to parts with unwanted collisions. For example, trimming tools need to follow a complicated motion to ensure they approach the edges being trimmed in the correct position and do not gouge the surrounding material. Humans use vision and tactile sensing to build mental models of objects.  Humans then use this model to generate and utilize complex tool motions. Tools may have cables and hoses attached to them. These appendages pose constraints on tool manipulation. Humans can account for these flexible objects when manipulating tools.    
  • Many manufacturing applications require working on large parts. For example, many parts used in marine vehicles can be larger than thirty feet. Humans need locomotion to complement their manipulation abilities and can use tools to work on significant parts.      
  •  For example, achieving the correct surface finish in polishing applications requires using the right tool rotational speed, pressure, and travel velocity. Humans learn how to use the right process parameters during the training process. They can learn new process parameters by experimenting with different materials.
  • Tool motion and process parameters must be adapted based on the observed performance during execution.  For example, as the sanding pad during the operation starts wearing out, the human operator will adjust the pressure and rotational speed to ensure that the tool delivers the expected performance. Humans have excellent visual, tactile, haptic, and auditory sensing abilities to adapt the tool based on the process performance.      

A large volume of work in robotics focuses on direct object manipulation, for example, where robots directly interact with objects using grippers. Most of the work in robotic material handling applications falls in this category. Object manipulation has its challenges. Manipulating objects with tools presents a different set of challenges for robots. Manipulating some tools is relatively simple. That is why several robotic screwdriver solutions are already available on the market. Unfortunately, robots in the past were unable to perform complex tool manipulation. This meant that many extremely tedious and ergonomically challenging tasks, such as sandblasting, were still performed by humans.                

The surface treatment area presents a substantial segment of manufacturing. Robots have been limited to mass-production applications that rely on humans to program them. Robots were able to execute pre-programmed motions.  

Unfortunately, we cannot rely on humans to program robots in high-mix surface treatment applications that require complex tool manipulation. High-mix surface treatment applications require robotic cells that can autonomously manipulate tools and match or exceed human performance.      

GrayMatter Robotics has developed physics-informed AI technology that enables smart robotic cells to automatically scan the parts placed in the cell and generate appropriate tool motions to meet process-specific requirements. Robotic manipulators can be mounted on gantries or mobile platforms to increase their reach and work on large parts. GMR-AI™ technology can easily handle an increase in the robot trajectory planning complexity due to using mobility platforms. GrayMatter Robotics is working with process experts to capture the process knowledge for various surface treatment applications. Smart robotic cells powered by GMR-AI™ technology also enable robotic cells to conduct experiments to refine the process parameters. Smart robotic cells utilize force and vision sensing to autonomously adapt the tool’s motion and control its interaction with the part to produce the desired quality.  

The same GMR-AI™ technology that powers GrayMatter Robotics’s award-winning product Scan&Sand™ also powers our new and future line of products and demonstrates that robots are beginning to master autonomous tool manipulation.

For more information on how our automated surface treatment solutions can work for you, please get in touch with us at  

By Satyandra SK Gupta, Chief Scientist and Co-Founder, GrayMatter Robotics

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