During his PhD program at the UCSD Coordinated Robotics Lab, Nick Morozovsky developed several dynamic robotic systems, including Switchblade, a balancing treaded platform, and SkySweeper, a novel cable-locomoting 3D-printed robot. In addition to describing the development process of these robots, and showing the prototypes, Nick will discuss trends in robotics technologies (microprocessors, 3D printing, etc.) that have made prototyping and developing robots faster and cheaper than ever.
Introduction to robotics, Laws,Classification,Types, Drives,Geometry Mohammad Ehtasham
Introduction to robotics , Basic overview ,Classification of robotics,laws of robotics,Types of robot, Robot Geometry, Robot drives, Some of the key benefits of robots in industry and society
What's going on with robots? What's coming next? From drones to autonomous vehicles, service robots, social robots or toys, here is a fairly broad overview.
Introduction to robotics, Laws,Classification,Types, Drives,Geometry Mohammad Ehtasham
Introduction to robotics , Basic overview ,Classification of robotics,laws of robotics,Types of robot, Robot Geometry, Robot drives, Some of the key benefits of robots in industry and society
What's going on with robots? What's coming next? From drones to autonomous vehicles, service robots, social robots or toys, here is a fairly broad overview.
This is part of a series of intro for quantum hardware and quantum circuit in Mandarin. The recordings can be found below:
https://www.youtube.com/watch?v=lSL7M6lzh_E
https://www.youtube.com/watch?v=XXM9-b9PzuY
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R, Data Wrangling & Kaggle Data Science CompetitionsKrishna Sankar
Presentation for my tutorial at Big Data Tech Con http://goo.gl/ZRoFHi
This is the R version of my pycon tutorial + a few updates
It is work in progress. I will update with daily snapshot until done.
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Slide shared is work of renowned Prof. Susanta Sen from Institute of Radio Physics and Electronics, University of Calcutta.
This was presented in NIT Patna by him on the occasion of Foundation day.
Slides contain great approach to VLSI technology from very basics and is really very helpful.
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This is part of a series of intro for quantum hardware and quantum circuit in Mandarin. The recordings can be found below:
https://www.youtube.com/watch?v=lSL7M6lzh_E
https://www.youtube.com/watch?v=XXM9-b9PzuY
James Birnie - Using Many Worlds of Compute Power with Quantum - Codemotion A...Codemotion
Quantum computers can use all of the possible pathways generated by quantum decisions to solve problems that will forever remain intractable to classical compute power. As the mega players vie for quantum supremacy and Rigetti announces its $1M "quantum advantage" prize, we live in exciting times. IBM-Q and Microsoft Q# are two ways you can learn to program quantum computers so that you're ready when the quantum revolution comes. I'll demonstrate some quantum solutions to problems that will forever be out of reach of classical, including organic chemistry and large number factorisation.
R, Data Wrangling & Kaggle Data Science CompetitionsKrishna Sankar
Presentation for my tutorial at Big Data Tech Con http://goo.gl/ZRoFHi
This is the R version of my pycon tutorial + a few updates
It is work in progress. I will update with daily snapshot until done.
This slide starts from a basic explanation between Bit and Qubit. It then follows with a brief history behind Quantum Computer, current trends, and update with concerns to make the quantum computer practically useful.
Solar System Processing with LSST: A Status UpdateMario Juric
An update for the LSST Solar System Science Collaboration on the work in progress on data products and software needed to support the Solar System science. Delivered at DPS 2017 meeting.
Presentation on machine learning and materials science at Computing in Engineering Forum 2018, Machine Ground Interaction Consortium (MaGIC) 2018, Wisconsin, Madison, December 4, 2018
Design World Webinar on Engineering tomorrow's robots and drones today. Challenges in robotics, robotics landscape, tools for rapid prototyping, sensors, simulation case study.
Slide shared is work of renowned Prof. Susanta Sen from Institute of Radio Physics and Electronics, University of Calcutta.
This was presented in NIT Patna by him on the occasion of Foundation day.
Slides contain great approach to VLSI technology from very basics and is really very helpful.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
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• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
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However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
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Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
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The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
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4. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Introduction
• Hardware revolution is underway
• Robotics is a subset, what is a robot anyway?
• Barriers to entry in developing hardware are
plummeting
• Driven by low-cost, capable components,
software tools, and global communications
• The line between hardware and software is being
blurred.
4
http://makezine.com/projects/make-43/smart-rat-trap/
5. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Introduction
• Proliferation of low-cost and capable
microprocessors and sensors
• 3D Robotics CEO Chris Anderson’s
“peace dividend of the smartphone war”
• Accelerometers, gyroscopes,
magnetometers, light sensors,
cameras, GPS, WiFi, Bluetooth, etc.
• Additive manufacturing (3D printing) has
dropped two orders of magnitude in price
• Rapid prototyping on your desk
5
6. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Introduction
6
from Cyril Ebersweiler’s Hardware trends 2015 slideshare
http://www.slideshare.net/haxlr8r/hardware-trends-2015
or search: slideshare hardware trends
7. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Introduction
Robotics Challenges
7
MobilityPerception
Manipulation
“Go get me a
beer from the
fridge”
Stairs
Opening
a door
Sand
Eggs
Unstructured
terrain
Where to
grasp object
Localization
Mapping
9. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Mechanical Engineering
• 3D printing
• Multiple materials are here,
and more are coming
• New generation of CAD tools
• TinkerCAD
• OpenSCAD
• Onshape
9
11. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Electrical Engineering
• Voxel8 Multi-material 3D printer
• Autodesk Project Wire
11
12. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Software Engineering
• Explosion of single board computers
• Arduino, Raspberry Pi, BeagleBone,
Spark, etc. communities
• Almost any sensor or actuator you’re
trying to interface has already been
interfaced
• Pay attention to licenses and be a
good community member
• ROS: Robot Operating System
12
13. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Funding
• Bootstrapping
• Accelerators/Incubators
• Increasing number of
hardware accelerators
13
14. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Crowdfunding
• Just posting on Kickstarter does not guarantee success!
14
15. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Crowdfunding
15
from Cyril Ebersweiler’s Hardware trends 2015 slideshare
http://www.slideshare.net/haxlr8r/hardware-trends-2015
or search: slideshare hardware trends
16. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Complementary Filter
• MEMS accelerometer can measure
absolute angle of gravity vector
• Susceptible to high frequency
noise and body accelerations
• MEMS gyroscope can be
integrated to measure incremental
angle
• Susceptible to thermal drift and
integration error
• Use complementary filter to
combine accelerometer and
gyroscope measurements
16
atan2
1/s
Low
Pass
High
Pass
s
Accelerometer
Gyroscope
Encoder
+
+
++
++ ˙
˙✓
✓
µGHP =
1/!c
1/!c + h
, µALP =
h
1/!c + h
17. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Encoder Velocity Estimation
• Limited by encoder and clock
resolution
• Quadrature sub-periods are not
equal
• Measure four separate periods
• Average multiple periods when
possible (M ≥ 2)
• Bound low speed by time since
last edge (M < 1)
17
A
ARF
B
AFR
BFR BRF
AR BR BR AF AF BF BF AR
ARR
BFF
M =
2!h CPR
⇡
18. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Lagrangian Dynamics
• Powerful dynamics
formulation
• Apply constraints with
Lagrange multiplier
• Broadly applicable to a
large class of robotic
systems
• Can be applied
programmatically
18
L = T V
d
dt
✓
L
˙qi
◆
L
qi
= Qi
M(q)¨q + F(q, ˙q) = Q
A(q) ˙q = 0
M(q)¨q + F(q, ˙q) = Q + A(q)T
S(q) = null[A(q)]
S(q)T
M(q)¨q + S(q)T
F(q, ˙q) = S(q)T
Q
19. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Lagrangian Dynamics
19
˙q = S⌫, ¨q = S ˙⌫, ST
M(q)S ˙⌫ + ST
F(q, ˙q) = ST
Q
˙⌫ = [ST
M(q)S] 1
ST
[Q F(q, ˙q)]
¨q = S[ST
M(q)S] 1
ST
[Q F(q, ˙q)]
Q = B⌧ = B[⌃u Z( ˙q)]
˙qr =
¯
S⌫, ¨qr =
¯
S ˙⌫, x =
✓
qr
˙qr
◆
, ˙x = f(x) + (x)u
f(x) =
✓
˙qr
¯
S[ST
M(q)S] 1
ST
[BZ( ˙q) + F(q, ˙q)]
◆
(x) =
✓
0n⇥nu
¯
S[ST
M(q)S] 1
ST
B⌃
◆
20. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Equilibrium Manifold
• Solve for (unstable) equilibrium manifold from dynamics by setting
accelerations and velocities to zero
• Equivalent to static analysis, setting Newton’s 2nd Law equal to zero and
setting center of mass over contact point
• u* is a feedforward term when the equilibrium requires non-zero control input
20
˙⌫ = [ST
M(q)S] 1
ST
{B[⌃u Z( ˙q)] F(q, ˙q)} = 0nr⇥1
ST
{B[⌃u⇤
Z(0n⇥1)] F(q⇤
, 0n⇥1)} = 0nr⇥1
˜x = x x⇤
, ˜u = u u⇤
˙˜x = f(˜x + x⇤
) + (˜x + x⇤
)(˜u + u⇤
)
21. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Tools
Linearization & Integral Control
• Linearize about
reference position
• Integrate regulation error
• Discretize with sample
time h
• State feedback matrix
from LQR
• Can be applied
programmatically
21
˙˜x =A˜x + B(˜u + u⇤
)
A =
f(˜x + x⇤
)
˜x ˜x=0
, B = (˜x + x⇤
)
˜x=0
˙⇠ =C˜x, ¯x =
✓
˜x
⇠
◆
, ˙¯x = A¯x + B(˜u + u⇤
)
A =
A 02n⇥nu
C 0ni⇥nu
, B =
B
0ni⇥nu
¯xk+1 =F ¯xk + G(˜uk + u⇤
)
F =eAh
, G =
Z h
0
eA⌘
Bd⌘
u =K
✓
x x⇤
⇠
◆
+ u⇤
23. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Switchblade
• Tread assemblies can pivot
w.r.t. the central chassis
• Significantly changes the
center of mass
• Different modes of locomotion
• Applications: search & rescue,
border patrol, mine exploration,
toy/entertainment, general
research platform
• Patent pending
23
24. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Switchblade
Perching Dynamics
• Constraint matrices combine no-slip condition and
different stiction states
• Power function accounts for rate of energy
dissipation due to coulomb friction
24
θ
α
ϕ
LT
LC
rmT
mC
w
mS
X
Yρ
w = r( ↵) ⇢(⇡/2 ↵)
P =
µkmgr
sin ↵
( ˙ ˙↵) cT ( ˙↵ ˙✓)
P
˙q
=
0
B
B
@
0
µkmgr
sin ↵ · sgn( ˙ ˙↵)
µkmgr
sin ↵ · sgn( ˙ ˙↵) cT · sgn( ˙↵ ˙✓)
cT · sgn( ˙↵ ˙✓)
1
C
C
A , q =
0
B
B
@
w
↵
✓
1
C
C
A
25. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Switchblade
Mechanical Design
• Two degree of freedom hip joint
• Two independent torques
transmitted coaxially
• Continuous rotation
• Motors, sensors, and battery in
chassis–simplifies wiring
• Leverage symmetry to reduce unique
part count
• Sheets of plastic laser cut into parts
• Tabs and slots speed up assembly and
reduce the number of fasteners needed
25
27. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Switchblade
Perching
• Friction compensator improves
performance
• Oscillation is due to stiction
• Performance limited by mass distribution
and friction
27
0 1 2 3 4 5 6 7 8 9 10
−0.5
0
0.5
1
1.5
2
T im e (sec)
Angle(rad)
φ
α
θ
φ∗
α ∗
θ ∗
0 1 2 3 4 5 6 7 8 9 10
−1.92
−1.9
−1.88
−1.86
−1.84
−1.82
−1.8
−1.78
−1.76
T im e (sec)
φ−α(rad)
0 1 2 3 4 5 6 7 8 9 10
−1
−0.5
0
0.5
1
T im e (sec)
˙φ−˙α(rad/sec)
Ex p erim ental a S = 0
Ex p erim ental a S = 0.06
Sim ulation a S = 0
Sim ulation a S = 0.06
φ∗
− α ∗
θ
α
ϕ
LT
LC
rmT
mC
w
mS
X
Yρ
29. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
SkySweeper
• 2 identical links pivotally
connected by rotary series
elastic actuator (SEA) hub
• 3 position actuated clamp
(a) Open
(b) Rolling - allows axial
translation
(c) Pivoting
• Presented at IROS 2013 in Tokyo
29
30. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
SkySweeper
Inchworm
• One pivoting clamp and one rolling clamp
• SEA actuates to increase the angle between the links
• Switch clamp configuration, decrease the angle between the links, repeat
30
31. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
SkySweeper
Swing-Up
• One pivoting clamp and
one open clamp
• Sine sweep control input
to the SEA
• Second clamp closes
once it reaches cable
• Useful for installation on
the cable
31
32. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
SkySweeper
Backflip
• One pivoting clamp and one open clamp
• Preload SEA, release one clamp, swing to grab other end, repeat
• Circumvent obstacle on the cable
32
33. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
𝜃
𝜶
x
y
JL ,mL
JL ,mL
JJ
2L
2L
1
2
SkySweeper
Dynamics
• Dynamic constraints depend on
the configuration of the clamps
• 0, 1, or 2 constraints per clamp
• Holonomic vertical constraint
when clamp is rolling or pivoting
• Additional non-holonomic
horizontal constraint when clamp
is pivoting
• Stack applicable constraint
matrices and find orthonormal
basis for null space
33
y = 0
Ay1(q) = (0 1 0 0 0)
˙x = 0
A˙x1(q) = (1 0 0 0 0)
y 2L(cos ✓ + cos ↵) = 0
Ay2(q) = (0 1 2L sin ✓ 0 2L sin ↵)
˙x + 2L( ˙✓ cos ✓ + ˙↵ cos ↵) = 0
A˙x2(q) = (1 0 2L cos ✓ 0 2L cos ↵)
q = x y ✓ ↵
T
34. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
SkySweeper
Finite State Machine Controller
• Actions: clamp positions, SEA
• Transitions defined by sensor
readings: spring deflection,
separation angle, cable
detection
• Implemented in code as a
switch structure
• Simulation performed with
switched system of equations
of motion with different
constraint matrices
𝜃+π-𝜶 > 1.9
𝜃+π-𝜶 < 1.0
State 0: Open
Clamp 1: Pivoting
Clamp 2: Rolling
u = -0.65
State 1: Close
Clamp 1: Rolling
Clamp 2: Pivoting
u = 0.40
State 8: Swing 1
Clamp 1: Pivoting
Clamp 2: Open
u = -0.20
State 9: Charge 2
Clamp 1: Pivoting
Clamp 2: Pivoting
u = 1
Cable in grasp of clamp 2
State 7: Charge 1
Clamp 1: Pivoting
Clamp 2: Pivoting
u = -1
𝜶-γ > 1
State 10: Swing 2
Clamp 1: Open
Clamp 2: Pivoting
u = 0.20
𝜶-γ < -1
Cable in grasp of clamp 1
34
State 5: Swing
Clamp 1: Pivoting
Clamp 2: Open
u = 0.7t*sin(π t)
State 6: Hold
Clamp 1: Pivoting
Clamp 2: Pivoting
u = 0
Cable in grasp of clamp 2
Inchworm
Swing-Up
Backflip
35. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
SkySweeper
Design
• 3D printed parts with off the shelf electronics
• 3 position actuated clamp
• Servo drives symmetrically coupled clamp arms
• Magnets align clamps, teeth prevent rotation in pivoting position
• IR emitter and phototransistor pair detect cable
• Series elastic actuator (SEA) hub
• DC motor and two unidirectional torsion springs
• Energy storage for dynamic maneuvers
• Potentiometers measure spring deflection and angle between links
35
41. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Conclusions
Nick’s Rules of Robotics
41
1. Never disassemble a working robot.
1. Always have a demo ready.
2. Video or it didn’t happen.
2. If it works the first time, you’re testing it wrong.
1. How good is good enough? Have defined metrics.
2. If you can’t measure it, you can’t control it.
3. When in doubt, lubricate.
42. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Conclusions
Nick’s Rules of Robotics
4. Never underestimate the estimation problem.
1. “but it works in simulation”
5. If specs for a part are listed differently in two places, they’re both wrong.
1. How can you validate it yourself? Or deal with uncertainty?
6. Glue, tape, and zip-ties are not engineering solutions (though they might work in
a pinch).
1. You should be able to open your robot.
2. The component that’s hardest to access will be the first to fail.
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43. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Conclusions
Nick’s Rules of Robotics
7. Do not leave lithium polymer batteries charging unattended.
1. It’s not worth the risk.
2. Use a charging sack.
8. Always have a complete CAD model, including screws and fasteners, before
constructing your robot.
1. Plan out order of operations for assembly.
2. Have extra parts on hand.
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44. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Conclusions
Nick’s Rules of Robotics
9. Avoid using slip rings if at all possible.
1. Intermittent contact, high/variable resistance
10.Clamping collars are always better than set screws.
1. If you have to use set screws (e.g. for cost reasons), use a driving flat
and an appropriate thread-locking agent.
11.Always check polarity before plugging a component into a power source.
1. Label battery connectors and components.
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ServoCity.com clamping hub
45. UCSD Coordinated
Robotics Lab
Nick Morozovsky Mar 17, 2015
Conclusions
Acknowledgments
• Advisor: Professor
Thomas Bewley
• Chris Schmidt-Wetekam,
Andrew Cavender
• Members of the
Coordinated Robotics Lab
at UCSD
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