Emerging 3D Vision Technologies for Industrial Robots

Jul 1, 2021

Learn about the emerging 3D vision technology that businesses are using for industrial robot applications.

Fanuc Vision Robot

As more indus­tries come to terms with the need for robots in their oper­a­tions, the num­ber of indus­tri­al robots installed world­wide will expe­ri­ence pos­i­tive growth with­in the next five years. With this devel­op­ing inter­est in automa­tion comes more invest­ments into research and devel­op­ment. The out­come is lean­er robot­ic sys­tems with more advanced com­po­nents. A grow­ing trend for robot­ic work­cells is 3D auto­mat­ic vision. This tech­nol­o­gy allows the robot to iden­ti­fy an object’s posi­tion, size, depth, and col­or. Sec­tors like logis­tics, food pro­cess­ing, life sci­ence, and man­u­fac­tur­ing are find­ing ways to auto­mate their process­es using visu­al components. 

What are the dif­fer­ent approach­es to 3D vision?

Vision tech­nol­o­gy is not a one size fits all” tool. Cer­tain fac­tors such as appli­ca­tion, equip­ment, prod­uct, envi­ron­ment, and bud­get will deter­mine how to inte­grate vision into the process. There is no stan­dard when it comes to set­ting up real-time 3D imag­ing in a robot­ic sys­tem. How­ev­er, there are a few stan­dard tech­niques used by vision-inte­gra­tion experts, each tai­lored to ben­e­fit spe­cif­ic tasks. These tech­niques are stereo vision, time-of-flight (TOF), laser tri­an­gu­la­tion, and struc­tured light. 

Laser Tri­an­gu­la­tion

Objects pass through a beam of light emit­ted by a laser scan­ner. A cam­era posi­tioned at a spe­cif­ic angle records an image of the laser line as the item pass­es through, dis­tort­ing the beam and cre­at­ing a pro­file of the object. 

Struc­tured light

A pro­jec­tor cre­ates a thin band of light to project a pat­tern on an object. Cam­eras from dif­fer­ent angles observe the var­i­ous curved lines from the light to devel­op a 3D image of the object. 

Time of Flight (ToF)

A cam­era uses a high-pow­er laser scan­ner to emit light reflect­ed from the object back to the image sen­sor. The dis­tance from the cam­era to the object is cal­cu­lat­ed based on the time delay between trans­mit­ted and received light.

Stereo vision

The robot­ic sys­tem uses two cam­eras to record the same 2D view of an object tak­en from two dif­fer­ent angles. The soft­ware then uses the estab­lished posi­tion of the two cam­eras and com­pares cor­re­spond­ing points in the two flat images to iden­ti­fy vari­a­tions and pro­duce an image.

What appli­ca­tions are using 3D robot­ic vision?

There is a need for the mod­ern indus­tri­al robot to detect objects, rec­og­nize parts, and grip com­po­nents at the right angle. While tra­di­tion­al robots are per­fect for locat­ing parts con­sis­tent­ly, mod­ern robot­ics can coor­di­nate cor­rec­tions to detect where the piece is. Instead of an entire pro­duc­tion line com­ing to a stop because sub­se­quent actions are not indef­i­nite order, the sys­tem quick­ly rec­og­nizes a change and adapts to it. As a result, an array of indus­tri­al appli­ca­tions across indus­tries invest in 3D robot­ic vision. These include the logis­tics, food pro­cess­ing, life sci­ence, man­u­fac­tur­ing, and auto­mo­tive indus­tries. With so many sec­tors automat­ing, the use of vision tech­nol­o­gy is expand­ing into new ter­ri­to­ry. Depal­letiz­ing appli­ca­tions use 3D vision com­po­nents to scan pal­lets filled with var­i­ous types of ship­ping box­es for sort­ing. They use scan­ners to send the image to soft­ware to allow the robot to detect box types based on tex­ture pat­terns and send them to des­ig­nat­ed areas. A food pro­cess­ing plant uses mul­ti­spec­tral vision tech and spe­cial light­ing to inspect the prod­uct and detect spoilage. Appli­ca­tions that have tra­di­tion­al­ly used vision tech­nol­o­gy are upgrad­ing to more inno­v­a­tive equip­ment. An aero­space com­pa­ny replaced tra­di­tion­al inspec­tion tools with 3D scan­ning to inspect tur­bine blades for imper­fec­tions, reduc­ing inspec­tion time from 18 hours to 45 min­utes. Vision tech­nol­o­gy will con­tin­ue to expand, with future trends pre­dict­ed in logis­tics appli­ca­tions, mul­ti­spec­tral machine vision, adap­tion using machine learn­ing with 3D vision, and liq­uid lens­es to allow more pre­cise images from greater distances. 

Cru­cial sub­sys­tems and com­po­nents for vision applications

The most coor­di­nat­ed automa­tion sys­tems have more than a sin­gle auto­mat­ed con­trol sys­tem and com­po­nents inte­grat­ed to make an effi­cient work­cell assem­bly. When it comes to incor­po­rat­ing advanced 3D vision options like object track­ing, prod­uct pro­fil­ing, and bin pick­ing into a process line, the sys­tem should gen­er­ate 3D imagery data. The use of 3D vision in robot­ic sys­tems requires inte­grat­ing var­i­ous com­po­nents to facil­i­tate ade­quate pow­er sup­ply, real-time pro­cess­ing, and safe­ty. Anoth­er crit­i­cal com­po­nent of suc­cess­ful automa­tion is com­mu­ni­ca­tion capa­bil­i­ty. It is good prac­tice in the dig­i­tal age to have con­nec­tiv­i­ty ports to dig­i­tal­ly con­nect a sys­tem to oth­er pieces of equip­ment for data shar­ing. Emerg­ing robot tech­nolo­gies facil­i­tate Wi-Fi con­nec­tiv­i­ty for the same pur­pose. At the design stage, dri­ving a risk assess­ment study is the only way to iden­ti­fy and remove prob­lems from a sys­tem that could risk mal­func­tion. A 3D vision-enabled robot can safe­ly stop equip­ment to pre­vent injury and dam­age to equip­ment. If buy­ers invest in the research and upfront plan­ning, the result will be a flex­i­ble and easy-to-use auto­mat­ed system. 


Mod­ern man­u­fac­tur­ing demands more out of less, with lean­er pro­duc­tion lines need­ing to pro­vide greater out­put. The influ­ence of robot­ic vision will con­tin­ue to expand into dif­fer­ent pro­duc­tion areas and find brand-new ways to improve auto­mat­ed process­es. Expect more 3D visu­al com­po­nents to become com­mon in auto­mat­ic sys­tems in the future. 

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