Edward L. Zhu
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View article: An Integrated Platform for High-Throughput Extraction and Mass Spectrometry-Based Quantification of Cholesterol and Sphingosine
An Integrated Platform for High-Throughput Extraction and Mass Spectrometry-Based Quantification of Cholesterol and Sphingosine Open
Quantification of cellular lipids in a reproducible and high-throughput manner is a key step in the development of therapeutics for lipid storage diseases. Niemann-Pick Disease Type C (NPC) is a genetic disorder characterized by the accumu…
View article: Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control
Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control Open
We introduce an Implicit Game-Theoretic MPC (IGT-MPC), a decentralized algorithm for two-agent motion planning that uses a learned value function that predicts the game-theoretic interaction outcomes as the terminal cost-to-go function in …
View article: A Sequential Quadratic Programming Approach to the Solution of Open-Loop Generalized Nash Equilibria for Autonomous Racing
A Sequential Quadratic Programming Approach to the Solution of Open-Loop Generalized Nash Equilibria for Autonomous Racing Open
Dynamic games can be an effective approach for modeling interactive behavior between multiple competitive agents in autonomous racing and they provide a theoretical framework for simultaneous prediction and control in such scenarios. In th…
View article: Learning Model Predictive Control with Error Dynamics Regression for Autonomous Racing
Learning Model Predictive Control with Error Dynamics Regression for Autonomous Racing Open
This work presents a novel Learning Model Predictive Control (LMPC) strategy for autonomous racing at the handling limit that can iteratively explore and learn unknown dynamics in high-speed operational domains. We start from existing LMPC…
View article: A Pose-Based Walking/Running Coach System for Cerebral Palsy Patients Using Artificial Intelligence and Computer Vision
A Pose-Based Walking/Running Coach System for Cerebral Palsy Patients Using Artificial Intelligence and Computer Vision Open
Cerebral palsy is a common motor disability that causes gait abnormalities. Clinical gait analysis is expensive and inaccessible. We investigated the research question: how can we create an affordable and effective method using AI to provi…
View article: Integration of landscape-level remote sensing and tree-level ecophysiology reveals drought refugia for a rare endemic, bigcone Douglas-fir
Integration of landscape-level remote sensing and tree-level ecophysiology reveals drought refugia for a rare endemic, bigcone Douglas-fir Open
For forest species, areas buffered from the rapidly increasing climate stressors and patterns of disturbance — i.e., climate change refugia — are important targets for conservation and protection. Here, we present a novel field survey and …
View article: Discovery and Optimization of Pyrrolopyrimidine Derivatives as Selective Disruptors of the Perinucleolar Compartment, a Marker of Tumor Progression toward Metastasis
Discovery and Optimization of Pyrrolopyrimidine Derivatives as Selective Disruptors of the Perinucleolar Compartment, a Marker of Tumor Progression toward Metastasis Open
The perinucleolar compartment (PNC) is a dynamic subnuclear body found at the periphery of the nucleolus. The PNC is enriched with RNA transcripts and RNA-binding proteins, reflecting different states of genome organization. PNC prevalence…
View article: A Gaussian Process Model for Opponent Prediction in Autonomous Racing
A Gaussian Process Model for Opponent Prediction in Autonomous Racing Open
In head-to-head racing, an accurate model of interactive behavior of the opposing target vehicle (TV) is required to perform tightly constrained, but highly rewarding maneuvers such as overtaking. However, such information is not typically…
View article: A Sequential Quadratic Programming Approach to the Solution of Open-Loop Generalized Nash Equilibria
A Sequential Quadratic Programming Approach to the Solution of Open-Loop Generalized Nash Equilibria Open
Dynamic games can be an effective approach to modeling interactive behavior between multiple non-cooperative agents and they provide a theoretical framework for simultaneous prediction and control in such scenarios. In this work, we propos…
View article: Distributed Learning Model Predictive Control for Linear Systems
Distributed Learning Model Predictive Control for Linear Systems Open
This paper presents a distributed learning model predictive control (DLMPC) scheme for distributed linear time invariant systems with coupled dynamics and state constraints. The proposed solution method is based on an online distributed op…
View article: Trajectory Optimization for Nonlinear Multi-Agent Systems using Decentralized Learning Model Predictive Control
Trajectory Optimization for Nonlinear Multi-Agent Systems using Decentralized Learning Model Predictive Control Open
We present a decentralized minimum-time trajectory optimization scheme based on learning model predictive control for multi-agent systems with nonlinear decoupled dynamics and coupled state constraints. By performing the same task iterativ…
View article: Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach
Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach Open
We present a hierarchical control approach for maneuvering an autonomous vehicle (AV) in tightly-constrained environments where other moving AVs and/or human driven vehicles are present. A two-level hierarchy is proposed: a high-level data…
View article: Trajectory Optimization for Nonlinear Multi-Agent Systems using\n Decentralized Learning Model Predictive Control
Trajectory Optimization for Nonlinear Multi-Agent Systems using\n Decentralized Learning Model Predictive Control Open
We present a decentralized minimum-time trajectory optimization scheme based\non learning model predictive control for multi-agent systems with nonlinear\ndecoupled dynamics and coupled state constraints. By performing the same task\nitera…
View article: Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots
Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots Open
Robots with flexible spines based on tensegrity structures have potential advantages over traditional designs with rigid torsos. However, these robots can be difficult to control due to their high-dimensional nonlinear dynamics and actuato…
View article: Rapidly Converting a Project-Based Engineering Experience for Remote Learning: Successes and Limitations of Using Experimental Kits and a Multiplayer Online Game
Rapidly Converting a Project-Based Engineering Experience for Remote Learning: Successes and Limitations of Using Experimental Kits and a Multiplayer Online Game Open
To provide a project-based learning experience during the COVID-19 outbreak, we mailed experimental kits to 285 undergraduate students and developed curriculum for a multi-player online robot simulation game. Students successfully achieved…
View article: Trajectory Tracking Control of a Flexible Spine Robot, With and Without a Reference Input
Trajectory Tracking Control of a Flexible Spine Robot, With and Without a Reference Input Open
The Underactuated Lightweight Tensegrity Robotic Assistive Spine (ULTRA Spine) project is an ongoing effort to develop a flexible, actuated backbone for quadruped robots. In this work, model-predictive control is used to track a trajectory…
View article: Model-Predictive Control with Inverse Statics Optimization for\n Tensegrity Spine Robots
Model-Predictive Control with Inverse Statics Optimization for\n Tensegrity Spine Robots Open
Robots with flexible spines based on tensegrity structures have potential\nadvantages over traditional designs with rigid torsos. However, these robots\ncan be difficult to control due to their high-dimensional nonlinear dynamics\nand actu…
View article: Model-Predictive Control with Reference Input Tracking for Tensegrity Spine Robots.
Model-Predictive Control with Reference Input Tracking for Tensegrity Spine Robots. Open
View article: Design, Simulation, and Testing of a Flexible Actuated Spine for Quadruped Robots
Design, Simulation, and Testing of a Flexible Actuated Spine for Quadruped Robots Open
Walking quadruped robots face challenges in positioning their feet and lifting their legs during gait cycles over uneven terrain. The robot Laika is under development as a quadruped with a flexible, actuated spine designed to assist with f…
View article: Design, Simulation, and Testing of Laika, a Quadruped Robot with a Flexible Actuated Spine.
Design, Simulation, and Testing of Laika, a Quadruped Robot with a Flexible Actuated Spine. Open
Walking quadruped robots face challenges in positioning their feet and lifting their legs during gait cycles over uneven terrain. Laika is a quadruped robot with a flexible, actuated spine designed to assist with foot movement and balance …
View article: Inclined Surface Locomotion Strategies for Spherical Tensegrity Robots
Inclined Surface Locomotion Strategies for Spherical Tensegrity Robots Open
This paper presents a new teleoperated spherical tensegrity robot capable of performing locomotion on steep inclined surfaces. With a novel control scheme centered around the simultaneous actuation of multiple cables, the robot demonstrate…
View article: Soft Spherical Tensegrity Robot Design Using Rod-Centered Actuation and Control
Soft Spherical Tensegrity Robot Design Using Rod-Centered Actuation and Control Open
This paper presents the design, analysis, and testing of a fully actuated modular spherical tensegrity robot for co-robotic and space exploration applications. Robots built from tensegrity structures (composed of pure tensile and compressi…