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Pavlo Manovi

dblp:164/8642 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Legged, aerial and field robots · 88% Motion planning and robot control · 12%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
field robotics
0.522016
The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2 · ICRA 2016
System design and locomotion of SUPERball, an untethered tensegrity robot · ICRA 2015
Robotics › Legged, aerial and field robots
locomotion
0.522016
The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2 · ICRA 2016
System design and locomotion of SUPERball, an untethered tensegrity robot · ICRA 2015
Robotics › Legged, aerial and field robots › bio-inspired robot
tensegrity robot
0.522016
The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2 · ICRA 2016
System design and locomotion of SUPERball, an untethered tensegrity robot · ICRA 2015
Robotics › Legged, aerial and field robots › locomotion
dynamic locomotion
0.212015
System design and locomotion of SUPERball, an untethered tensegrity robot · ICRA 2015
Robotics › Motion planning and robot control
robot control
0.122016
The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2 · ICRA 2016
System design and locomotion of SUPERball, an untethered tensegrity robot · ICRA 2015
Robotics › Motion planning and robot control › multi-robot control
synchronization control
0.112016
The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2 · ICRA 2016

Methods — techniques the papers use, named apart from their topics

dynamic simulation · 0.2trajectory tracking · 0.2tensegrity structure · 0.2
YearPublicationVenuePosition
2016 The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2
abstract
Duct exploration and maintenance is a task well suited for small agile robots, which must be capable of navigating complex and irregular systems of ducts. Previously, we presented a tensegrity robot, DuCTT (Duct Climbing Tetrahedral Tensegrity), which demonstrated the plausibility of such a robot for duct exploration but was never able to successfully demonstrate climbing. Here we present DuCTTv2, redesigned from the ground up to address issues with actuator power, cable routing, compliance and synchronized control present in our first prototype. These improvements allow the prototype to be the first tensegrity robot to demonstrate duct climbing, and does so with an average climb speed of 1.4 cm/s. We also demonstrate initial tests of the prototypes ability to bend and translate its two segments relative to one another, which will allow it to navigate T-junctions and sharp corners commonly found in duct systems. Testing of the prototype is conducted to demonstrate the new faster and more robust control of motion, and analysis of dynamic simulations is presented.
Jeffrey M. Friesen, Paul Glick, Michael Fanton, Pavlo Manovi, Alexander Xydes, Thomas R. Bewley, Vytas SunSpiral
ICRA4
2015 System design and locomotion of SUPERball, an untethered tensegrity robot
abstract
The Spherical Underactuated Planetary Exploration Robot ball (SUPERball) is an ongoing project within NASA Ames Research Center's Intelligent Robotics Group and the Dynamic Tensegrity Robotics Lab (DTRL). The current SUPERball is the first full prototype of this tensegrity robot platform, eventually destined for space exploration missions. This work, building on prior published discussions of individual components, presents the fully-constructed robot. Various design improvements are discussed, as well as testing results of the sensors and actuators that illustrate system performance. Basic low-level motor position controls are implemented and validated against sensor data, which show SUPERball to be uniquely suited for highly dynamic state trajectory tracking. Finally, SUPERball is shown in a simple example of locomotion. This implementation of a basic motion primitive shows SUPERball in untethered control.
Andrew P. Sabelhaus, Jonathan Bruce, Ken Caluwaerts, Pavlo Manovi, Roya Fallah Firoozi, Sarah Dobi, Alice M. Agogino, Vytas SunSpiral
ICRA4