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Samuel Jensen-Segal

dblp:30/3130 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2008
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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
1 paper
Legged, aerial and field robots · 67% Robot navigation and mapping · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
field robotics
0.112008
ROCR: Dynamic vertical wall climbing with a pendular two-link mass-shifting robot · ICRA 2008
Robotics › Legged, aerial and field robots › field robotics
wall-climbing robot
0.112008
ROCR: Dynamic vertical wall climbing with a pendular two-link mass-shifting robot · ICRA 2008

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

simulation · 0.1bio-inspired design · 0.1
YearPublicationVenuePosition
2008 ROCR: Dynamic vertical wall climbing with a pendular two-link mass-shifting robot
abstract
We present a novel bio-inspired dynamic climbing robot, with a recursive name: ROCR is an Oscillating Climbing Robot. ROCR is a pendular two-link, serial chain robot that utilizes alternating hand-holds and an actuated tail to propel itself upward in a climbing style based on observation of human climbers and brachiating gibbons. ROCR's bio-inspired oscillating climbing strategy is simple and efficient. This robot is intended for autonomous surveillance and inspection on sheer vertical surfaces. Potential locomotion gait strategies were investigated in simulation using Working Model 2D. Strategy comparisons were drawn on a basis of climbing rate and energy efficiency. Simulation results show the feasibility and relative merits of these climbing gait strategies and compare them to the potential energy gained while climbing. A first generation ROCR design, having physical parameters based on simulation analysis, that utilizes actuated permanent magnet grippers and a geared-motor actuated tail was fabricated. Magnetic grippers are used for this initial prototype to facilitate investigating the robots climbing efficiency. Several climbing gaits which showed promise in simulation were implemented in the prototype. ROCR is a lightweight, flexible, self-contained robot with onboard microcontroller, tilt and acceleration sensing, power supply and wireless communication. We conclude with plans to evolve the simulation and design of the robot and plans for testing the prototype.
Samuel Jensen-Segal, Steven Virost, William R. Provancher
ICRA1