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UID:10008410-1753106400-1753110000@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis: "Geometric Methods for Efficient and Explainable Control of Underactuated Robotic Systems"
DESCRIPTION:Robots are complex\, high-dimensional systems\, governed by nonlinear\, underactuated dynamics and evolving on non-Euclidean manifolds\, posing numerous challenges for control synthesis and analysis. While optimization-based methods of control can flexibly accommodate diverse dynamics\, costs\, and constraints\, they often demand coarse approximations or powerful onboard processors (infeasible for many aerial and space systems) due to their relatively poor computational efficiency. Although learned controllers can generally cope with more moderate onboard resources\, the computational burden of offline training is heavy\, and both the training pipeline and the policy obtained are often brittle. Conversely\, explicit control laws designed analytically often have miniscule computational overhead and perform robustly\, but they are typically only applicable to individual systems or a narrow class\, limiting their broader usefulness. \nNonetheless\, robots are not black-box nonlinear control systems—rather\, their dynamics enjoy powerful properties (e.g.\, symmetry and mechanical structure) that can be leveraged to gain traction on control design problems. In this thesis\, we explore the role of geometric methods in mitigating many of the above drawbacks\, across both analytical and data-driven methods. We study the role of symmetry in identifying effective abstractions for trajectory planning in underactuated mechanical systems (in particular\, “flat outputs”) and explore applications to task space planning for aerial manipulation. We also develop methods for synthesizing tracking controllers for mechanical systems evolving on the general class of homogeneous Riemannian manifolds\, and give certificates for the almost global asymptotic stability of cascades\, which often appear in the closed-loop dynamics of hierarchical controllers for underactuated systems. Lastly\, we leverage symmetry to accelerate training of tracking controllers via reinforcement learning (by constructing “continuous MDP homomorphisms”)\, also improving converged performance. \nIn all these methods\, a geometric perspective enables us to explainably construct abstractions that reduce dimensionality\, enforce structure\, and capture essential properties\, all the while representing the system or problem in a form more convenient for analysis or design. In contrast to ad hoc methods\, such reduced representations typically improve computational efficiency\, while also encouraging generality over a broader class of systems and affording insight into why prior handcrafted approaches were successful for particular cases. Sometimes\, such realizations also guide mechanical design\, closing the control-morphology feedback loop and leading to synergies between a robot’s embodiment and its controller. By combining explainable abstractions with scalable computation\, such methods build towards a future in which robotic systems move through their surroundings as capably and dynamically as their counterparts in Nature.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-geometric-methods-for-efficient-and-explainable-control-of-underactuated-robotic-systems/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
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DTSTART;TZID=America/New_York:20250722T101500
DTEND;TZID=America/New_York:20250722T111500
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CREATED:20250709T180609Z
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UID:10008409-1753179300-1753182900@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Exploring Jet-Propelled Soft Robots: Design\, Experiments\, and Theory"
DESCRIPTION:Understanding how marine animals migrate is critical for assessing the impacts of climate change on ocean ecosystems—and yet current Autonomous Underwater Vehicles (AUVs)\, with their noisy propellers and rigid hulls\, are ill-suited to operate alongside sensitive species. Bio-inspired robots offer a promising alternative by emulating the natural locomotion strategies of fish\, cephalopods\, and other marine organisms; however\, most existing prototypes still fall short of their biological counterparts in speed\, and energy efficiency—highlighting a significant performance gap. \nIn this talk\, I will focus on one specific locomotion—jet propulsion—and present our efforts to narrow that gap. First\, I will introduce our squid-inspired underwater robotic system and its evolution over the past few years\, discussing experiments and theoretical models that show how design and control parameters influence its performance. Next\, building on the squid-inspired robot platform\, we developed a salp-inspired robot with an additional frontal nozzle; experiments are conducted between the two robots to compare their performances and theoretical explanations are proposed to address the differences. Finally\, I will talk about our recently developed swivel-nozzle steering mechanism and describe our plan for achieving controlled two-dimensional navigation.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-exploring-jet-propelled-soft-robots-design-experiments-and-theory/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
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