Programming robots to help them perform human-specific tasks with Reinforcement and Imitation Learning algorithms. Robots are trained in virtual environments created in Unity using Imitation Learning from a human motion capture data. During reinforcement we used a Proximal Policy Optimization to allow robot to come up with most efficient and accurate way of performing a particular task. Later on trained neural network is reinforced by couple of minutes training in a real environment.

1. Humane RoboticsAllowing robots to perform human-level tasks.

2. Usage of Machine Learning based
Robotics is inevitable for all kinds
of industries in the next decade,
so societies and governments
should prepare for that.
ROBOTS FOR SOCIETIES
OUR VISION

3. KNOWING THE PROBLEMS
ROBOTIC
INTEGRATION
It's hard to integrate
robots into processes/
often you need to switch
to new application suite
PROGRAMMING
COSTS
It's expensive to
program or reprogram
the robots accordingly
to your needs
ROBOTS DO
SIMPLE TASKS
Robots can't (easily)
perform dynamically
changing tasks, so it’s
hard to use them in
most businesses

4. BIG PICTURE
• CONVERGENCE of IoT, ML/AI and ROBOTICS!
• IoT integration - additional data for decision making processes
• Artificial Intelligence - extracting expert knowledge
• Robotics - used in a high risk contexts/areas

5. BIG PICTURE
• CONVERGENCE of IoT, ML/AI and ROBOTICS!
• IoT integration - additional data for decision making processes
• Artificial Intelligence - extracting expert knowledge
• Robotics - used in a high risk contexts/areas
•LEASABLE FLEXIBLE AND DYNAMICALLY
ADAPTABLE PRODUCTION LINES

6. Our SOLUTION
Empowering SME with flexible
production lines
Robotic demonstrations of human-level
tasks
Self-training with Imitation and
Reinforcement Learning algorithms
Unity based simulation trainings of ROS
compatible robotics

7. Prototype

8. MARKET size
40 Billion USD >20% <5
Market Value by 2020
Growth of Robotic and AI markets
European countries
observe significant
integration of robotics

9. R o b o t U n i o n
a p p l i c a t i o n
A s s u m p t i o n s
v a l i d a t i o n s &
f e a s i b i l i t y
p l a n
p r e p a r a t i o n
M V P
D E V E L O P M E N T
ACTION PLAN
P R O T Y P E
( n o w )
U n i t y t ra i n i n g p i p e l i n e w i t h
R e i n f o r ce m e n t L e a r n i n g
S e e d i n ve s t m e n t ( 2 0 0 K E U R )
f o u n d e r s g o f u l l t i m e a n d
h i r e key e m p l oye e s

10. R o u n d A
i n v e s t m e n t
E U R O P E
e x p a n s i o n
N e x t r o u n d o r
C r o w d f u n d i n g
1-2 M EUR to build sales,
customer support team,
L E A S A B L E
F L E X I B L E
P R O D U C T I O N
L I N E S
ACTION PLAN

11. COMPETITION
ANALYSIS
Large players (NVIDIA)
- not interested in niches, slow in pivoting
Research centres (OpenAI, Universities)
- not focused on business problems
Small startups (NoMagic.AI)
- working in different niche

12. Chris Wrobel
CEO/CTO
MEET OUR TEAM
Bartek Wasilewski
CFO
Arek Kwoska
LinkedIn
Ralph Talmont
LinkedIn
ADVISORS
… and a bunch of
skilled freelancers
and consultants.

13. L E T ’ S TA L K !
C O N TA C T W I T H U S
C H R I S @ V R AT I O N A L . C O M