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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Iterated Local Search Algorithms For Bike Route Generation, Aidan Pieper
Iterated Local Search Algorithms For Bike Route Generation, Aidan Pieper
Honors Theses
Planning routes for recreational cyclists is challenging because they prefer longer more scenic routes, not the shortest one. This problem can be modeled as an instance of the Arc Orienteering Problem (AOP), a known NP-Hard optimization problem. Because no known algorithms exist to solve this optimization problem efficiently, we solve the AOP using heuristic algorithms which trade accuracy for speed. We implement and evaluate two different Iterated Local Search (ILS) heuristic algorithms using an open source routing engine called GraphHopper and the OpenStreetMap data set. We propose ILS variants which our experimental results show can produce better routes at the …
2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger
2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger
Honors Theses
The goal of this Senior Capstone Project was to lead Union College’s first ever Signal Processing Cup Team to compete in IEEE’s 2018 Signal Processing Cup Competition. This year’s competition was a forensic camera model identification challenge and was divided into two separate stages of competition: Open Competition and Final Competition. Participation in the Open Competition was open to any teams of undergraduate students, but the Final Competition was only open to the three finalists from Open Competition and is scheduled to be held at ICASSP 2018 in Calgary, Alberta, Canada. Teams that make it to the Final Competition will …
Optimizing Tensegrity Gaits Using Bayesian Optimization, James Boggs
Optimizing Tensegrity Gaits Using Bayesian Optimization, James Boggs
Honors Theses
We design and implement a new, modular, more complex tensegrity robot featuring data collection and wireless communication and operation as well as necessary accompanying research infrastructure. We then utilize this new tensegrity to assess previous research on using Bayesian optimization to generate effective forward gaits for tensegrity robots. Ultimately, we affirm the conclusions of previous researchers, demonstrating that Bayesian optimization is statistically significantly (p < 0:05) more effective at discovering useful gaits than random search. We also identify several flaws in our new system and identify means of addressing them, paving the way for more effective future research.
A Better Way To Construct Tensegrities: Planar Embeddings Inform Tensegrity Assembly, Elizabeth Anne Ricci
A Better Way To Construct Tensegrities: Planar Embeddings Inform Tensegrity Assembly, Elizabeth Anne Ricci
Honors Theses
Although seemingly simple, tensegrity structures are complex in nature which makes them both ideal for use in robotics and difficult to construct. We work to develop a protocol for constructing tensegrities more easily. We consider attaching a tensegrity's springs to the appropriate locations on some planar arrangement of attached struts. Once all of the elements of the structure are connected, we release the struts and allow the tensegrity to find its equilibrium position. This will allow for more rapid tensegrity construction. We develop a black-box that given some tensegrity returns a flat-pack, or the information needed to perform this physical …