in the 1960s unum 8 became the first

digital and programmable robot to

replace humans in an industrial factory

in 1961 it was installed at General

Motors and it carried out assembly line

tasks that were dangerous for humans

like picking up hot metals you know mate

was basically a big mechanical are much

less advanced than some of the tech we

have today but even now robots are often

built to perform the dangerous mundane

or difficult tasks humans perform to do

that a lot of these machines are

developed to physically replicate our

actions and behavior to have things like

a bipedal balanced walk a large range of

motion and the ability to perceive and

interact with the environment but maybe

not to your surprise that is a lot more

difficult to replicate than some viral

robot videos might make you think and

without these five groundbreaking

inventions much of modern robotics would

not be possible one of humanity's most

noteworthy traits is our ability to

sense our physical environment and react

intelligently to that information

I mean sometimes our brains are

constantly working to synthesize input

from things like our eyes nose skin and

even internal organs robots however work

on a much simpler level in many cases

the main information we need them to

understand and respond to is visual for

instance is the path to their

destination open where is something in

the way can they climb over that thing

or move it to make these decisions

robots use machine vision which uses

cameras and image processing algorithms

to measure and inspect the environment

the first image processing programs that

were applied to real-life images and

environments came around in the 1970s

but they were pretty inefficient since

then advances with both cameras and

image processing have caused some major

breakthroughs in machine vision today

robots can use multiple 3d and 2d

cameras to sense the world around them

and those images can be processed and

analyzed to detect

objects this information is communicated

to the brain or the robots centralized

computer which then decides based on its

programming what action it should take

this kind of Tech has allowed robotics

to move forward by leaps and bounds and

today it's often used on assembly lines

for quality control but it also has some

more flashy applications for example on

an Irving Lee cute robot called pepper

uses its machine vision for social

purposes it uses complex algorithms to

analyze the facial expressions of people

around it and it can guess emotions and

modify its conversation tactics as a

result because of its unique skills

pepper is being snapped up for use in

customer service to help customers

resolve simple easily solved issues a

human isn't needed for with machine

vision we can build robots that can

accurately see and respond to their

environment but that alone isn't enough

to be practical for robots to really

mimic and help us we also need them to

monitor their worlds continuously

especially if the robot moves that way

they can detect if something blocks

their path and adjust accordingly and

that brings us to our second innovation

robots that can monitor their world like

this are said to have closed-loop

control that means they're constantly on

the lookout for changes and can update

their internal maps and actions if new

obstacles arise now this general idea

has been around for a long time like

watchmakers we're building things with

closed-loop control in the 18th century

but it continued to grow as engineering

advanced nowadays we have amazing

computers with huge processing

capabilities and pretty efficient

algorithms and they're great at

calculating and incorporating feedback

this is helpful to stop robots from say

running into people but it's also super

important for simple things like keeping

a robot balanced as it moves the machine

needs constant feedback about its weight

distribution so that it can adjust its

alignment and center of gravity and not

fall over which honestly a lot of robots

fail at it's really hard for them to

navigate precisely and small errors and

calculations or coding bugs can cause

big problems in locomotion to achieve

balance and self

the most advanced robots are absolutely

decked out in sensors which measure

everything from weight to temperature to

posture and that helps them achieve

their incredibly dexterous human-like

movements a great example of this is

NASA's Valkyrie robots engineers began

developing Valkyrie in 2013 and they

originally intended it as an emergency

response robot but now it's been

redeveloped to one day set up habitats

on Mars prior to human arrival to help

us Valkyrie would have to perform a

number of detailed tasks without any

help like picking up boxes and walking

up stairs and to do this it is covered

in sensors like there are dozens of them

in Valkyries hands alone which is why

it's fine motor skills are so advanced

for a bot so although this thing is a

long way from the Red Planet it's still

one of the coolest robots being

developed today closed loop systems are

consistently becoming more advanced as

we develop faster more powerful

computers to help them with their

calculations but of course the computers

aren't the only factor here control

theory in general is still being

developed which means there might be

some fundamental lessons left to learn

so someday robots like Valkyrie might

just be the norm now just because your

robot has closed-loop control doesn't

mean it can move like a human after all

it might be able to adjust its position

in real time but that doesn't mean it

has the grace that we do reducing that

kind of fluid motion is actually one of

the unique obstacles for many robots and

it's an important one we need robots to

have precise motions so they can do

tasks that require a little finesse like

holding a glass beaker or even shaking

someone's hand if you have the power to

crush a person's hand you don't want to

make a mistake here a lot of robots are

getting closer to this fine movement

with the help of modern linear actuators

an actuator is a mechanical component

that converts energy into physical

motion and a linear actuator is one that

focuses on creating precise forces in a

single direction many actuators use a

hydraulic or pneumatic force which uses

pressurized fluids or gases to create

large amounts of energy whatever the

last

Gator so there have been great

improvements in electromechanical linear

actuators to ones that use electric

motors to produce motion their size cost

and energy usage have been significantly

reduced compared to other types of

actuators and that's allowed us to pack

more punch into a smaller area having

smaller and more precise actuators

allows for more degrees of freedom and

finer control of the robotic appendage

so by combining these pieces in just the

right way you can get a robot that moves

with almost eerie fluid grace if you

want to see an example for yourself you

should watch a video of Boston Dynamics

humanoid robot Atlas it uses four

hydraulic limbs 28 hydraulic joints and

numerous actuators to perform acrobatic

jumps somersaults other robot parkour

it's pretty cool we will have a link in

the description as you might guess

modern robots have a lot of working

parts and 3d printed ones are becoming

more and more commonplace for 3d

printing machine parts were generally

made either by pouring material into a

mold or by removing material to achieve

a desired shape but in 2009 a key patent

for a type of 3d printing expired and

the market began to grow as new

companies were finally able to develop

and release 3d printers since then this

kind of construction has been really

picking up steam because of its ability

to cheaply and quickly produce uniquely

constructed parts with a high

strength-to-weight ratio in other words

they're both light and strong which is

ideal for building robots in 3d printing

different ratios are achieved by using

filaments with different properties

thermoplastics like polycarbonate are

often used because the long chains of

molecules are durable and very easy to

manipulate at high temperatures the

chains of molecules are very loosely

packed now high temperatures their

chemical bonds quickly break down in the

material liquefies this pliability

allows engineers to precisely design

objects and optimize them for

load-bearing so their robots can be as

sturdy and strong as possible you can

find 3d printed parts in all kinds of

machines but to go back to a previous

example Atlas from Boston dynamic

is able to achieve such unique movement

partly thanks to its 3d printed parts

they allow the bot to be light enough to

do all those cool flips finally let's

wrap up with one of the most exciting

and ongoing advancements in robotics the

development of deep learning algorithms

these algorithms allow robots to not

only sense and react to their immediate

environment but also to remember and

recall past experiences to help inform

future decisions in the past

classical programming used static

directions to inform robot

decision-making rules like if you arrive

at a fork in the road always turn right

but deep learning algorithms take this

one step further they use accumulated

experiences to modify their directions

for example after turning right and

walking into a bunch of walls they might

revise their programming to make a rule

if you arrive at a fork in the road

always turn right unless there is an

obstacle the biggest advancement in deep

learning is the implementation of neural

networks inspired by neurons in the

brain these networks are made up of

computer nodes that store information

and send it to other nodes a neural

network gradually adjusts the weight

assigned to each signal as it maps

inputs to the correct outputs the more

weight a signal has the more it will

affect decisions in other parts of the

robots programming using neural networks

robots can put more weight into choices

that result in a positive outcome

allowing them to remember good decisions

and preferentially perform those actions

later most robots being developed today

have some form of deep learning

algorithm integrated into their hardware