Publications (45)
Performance guarantees for greedy maximization of non-submodular controllability metrics
Tyler Summers, Maryam Kamgarpour
A key problem in emerging complex cyber-physical networks is the design of information and control topologies, including sensor and actuator selection and communication network des…
Optimizing Weighted Hodge Laplacian Flows on Simplicial Complexes
Mathias Hudoba de Badyn, Tyler Summers
Simplicial complexes are generalizations of graphs that describe higher-order network interactions among nodes in the graph. Network dynamics described by graph Laplacian flows hav…
Sparse optimal control of networks with multiplicative noise via policy gradient
Benjamin Gravell, Yi Guo, Tyler Summers
We give algorithms for designing near-optimal sparse controllers using policy gradient with applications to control of systems corrupted by multiplicative noise, which is increasin…
Stochastic Optimal Power Flow Based on Data-Driven Distributionally Robust Optimization
Yi Guo, Kyri Baker, Emiliano Dall'Anese +2
We propose a data-driven method to solve a stochastic optimal power flow (OPF) problem based on limited information about forecast error distributions. The objective is to determin…
HRT1: One-Shot Human-to-Robot Trajectory Transfer for Mobile Manipulation
Sai Haneesh Allu, Jishnu Jaykumar P, Ninad Khargonkar +3
We introduce a novel system for human-to-robot trajectory transfer that enables robots to manipulate objects by learning from human demonstration videos. The system consists of fou…
Motion Planning with Precedence Specifications via Augmented Graphs of Convex Sets
Shilin You, Gael Luna, Juned Shaikh +4
We present an algorithm for planning trajectories that avoid obstacles and satisfy key-door precedence specifications expressed with a fragment of signal temporal logic. Our method…
Performance bounds for optimal feedback control in networks
Tyler Summers, Justin Ruths
Many important complex networks, including critical infrastructure and emerging industrial automation systems, are becoming increasingly intricate webs of interacting feedback cont…
Optimal Pump Control for Water Distribution Networks via Data-based Distributional Robustness
Yi Guo, Shen Wang, Ahmad Taha +1
In this paper, we propose a data-based methodology to solve a multi-period stochastic optimal water flow (OWF) problem for water distribution networks (WDNs). The framework explici…
On infinite dimensional linear programming approach to stochastic control
Maryam Kamgarpour, Tyler Summers
We consider the infinite dimensional linear programming (inf-LP) approach for solving stochastic control problems. The inf-LP corresponding to problems with uncountable state and i…
Grasping Trajectory Optimization with Point Clouds
Yu Xiang, Sai Haneesh Allu, Rohith Peddi +2
We introduce a new trajectory optimization method for robotic grasping based on a point-cloud representation of robots and task spaces. In our method, robots are represented by 3D…
Identification of Linear Systems with Multiplicative Noise from Multiple Trajectory Data
Yu Xing, Benjamin Gravell, Xingkang He +2
The paper studies identification of linear systems with multiplicative noise from multiple-trajectory data. An algorithm based on the least-squares method and multiple-trajectory d…
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
Matilde Gargiani, Andrea Zanelli, Andrea Martinelli +2
Despite their success, policy gradient methods suffer from high variance of the gradient estimate, which can result in unsatisfactory sample complexity. Recently, numerous variance…
Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking: Extended Version
Yitian Chen, Timothy L. Molloy, Tyler Summers +1
In this paper, we propose and analyze a new method for online linear quadratic regulator (LQR) control with a priori unknown time-varying cost matrices. The cost matrices are revea…
Centralized Collision-free Polynomial Trajectories and Goal Assignment for Aerial Swarms
Benjamin Gravell, Tyler Summers
Computationally tractable methods are developed for centralized goal assignment and planning of collision-free polynomial-in-time trajectories for systems of multiple aerial robots…
Minimax Iterative Dynamic Game: Application to Nonlinear Robot Control Tasks
Olalekan Ogunmolu, Nicholas Gans, Tyler Summers
Multistage decision policies provide useful control strategies in high-dimensional state spaces, particularly in complex control tasks. However, they exhibit weak performance guara…
Robust Control Design for Linear Systems via Multiplicative Noise
Benjamin Gravell, Peyman Mohajerin Esfahani, Tyler Summers
Robust stability and stochastic stability have separately seen intense study in control theory for many decades. In this work we establish relations between these properties for di…
The Linear Programming Approach to Reach-Avoid Problems for Markov Decision Processes
Nikolaos Kariotoglou, Maryam Kamgarpour, Tyler Summers +1
One of the most fundamental problems in Markov decision processes is analysis and control synthesis for safety and reachability specifications. We consider the stochastic reach-avo…
Stochastic Dynamic Programming for Wind Farm Power Maximization
Yi Guo, Mario Rotea, Tyler Summers
Wind farms can increase annual energy production (AEP) with advanced control algorithms by coordinating the set points of individual turbine controllers across the farm. However, i…
Learning robust control for LQR systems with multiplicative noise via policy gradient
Benjamin Gravell, Peyman Mohajerin Esfahani, Tyler Summers
The linear quadratic regulator (LQR) problem has reemerged as an important theoretical benchmark for reinforcement learning-based control of complex dynamical systems with continuo…
Solving Optimal Power Flow for Distribution Networks with State Estimation Feedback
Yi Guo, Xinyang Zhou, Changhong Zhao +3
Conventional optimal power flow (OPF) solvers assume full observability of the involved system states. However, in practice, there is a lack of reliable system monitoring devices i…
Sparse Structure Design for Stochastic Linear Systems via a Linear Matrix Inequality Approach
Yi Guo, Ognjen Stanojev, Gabriela Hug +1
In this paper, we propose a sparsity-promoting feedback control design for stochastic linear systems with multiplicative noise. The objective is to identify a sparse control archit…
Approximate Midpoint Policy Iteration for Linear Quadratic Control
Benjamin Gravell, Iman Shames, Tyler Summers
We present a midpoint policy iteration algorithm to solve linear quadratic optimal control problems in both model-based and model-free settings. The algorithm is a variation of New…
Self-Tuning Network Control Architectures with Joint Sensor and Actuator Selection
Karthik Ganapathy, Iman Shames, Mathias Hudoba de Badyn +1
We formulate a mathematical framework for designing a self-tuning network control architecture, and propose a computationally-feasible greedy algorithm for online architecture opti…
Risk Bounded Nonlinear Robot Motion Planning With Integrated Perception & Control
Venkatraman Renganathan, Sleiman Safaoui, Aadi Kothari +3
Robust autonomy stacks require tight integration of perception, motion planning, and control layers, but these layers often inadequately incorporate inherent perception and predict…
Actuator Placement for Optimizing Network Performance under Controllability Constraints
Baiwei Guo, Orcun Karaca, Tyler Summers +1
With the rising importance of large-scale network control, the problem of actuator placement has received increasing attention. Our goal in this paper is to find a set of actuators…
Self-Tuning Network Control Architectures
Tyler Summers, Karthik Ganapathy, Iman Shames +1
We formulate a general mathematical framework for self-tuning network control architecture design. This problem involves jointly adapting the locations of active sensors and actuat…
Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +2
We consider max-min and min-max problems with objective functions that are possibly non-smooth, submodular with respect to the minimiser and concave with respect to the maximiser.…
Build Once, Monitor Continuously: Persistent Semantic Mapping via Autonomous Exploration and Open-Vocabulary Object Updates
Sai Haneesh Allu, Itay Kadosh, Tyler Summers +1
Persistent semantic monitoring of indoor spaces such as warehouses, hospitals, and offices requires a robot to repeatedly monitor an environment and track how objects change over t…
Information Structure Design in Team Decision Problems
Tyler Summers, Changyuan Li, Maryam Kamgarpour
We consider a problem of information structure design in team decision problems and team games. We propose simple, scalable greedy algorithms for adding a set of extra information…
Data-driven distributionally robust MPC for systems with uncertain dynamics
Francesco Micheli, Tyler Summers, John Lygeros
We present a novel data-driven distributionally robust Model Predictive Control formulation for unknown discrete-time linear time-invariant systems affected by unknown and possibly…
Probabilistic Data Association for Semantic SLAM at Scale
Elad Michael, Tyler Summers, Tony A. Wood +2
With advances in image processing and machine learning, it is now feasible to incorporate semantic information into the problem of simultaneous localisation and mapping (SLAM). Pre…
Topology Design for Optimal Network Coherence
Tyler Summers, Iman Shames, John Lygeros +1
We consider a network topology design problem in which an initial undirected graph underlying the network is given and the objective is to select a set of edges to add to the graph…
CLIPPER+: A Fast Maximal Clique Algorithm for Robust Global Registration
Kaveh Fathian, Tyler Summers
We present CLIPPER+, an algorithm for finding maximal cliques in unweighted graphs for outlier-robust global registration. The registration problem can be formulated as a graph and…
Distributionally Robust Bootstrap Optimization
Tyler Summers, Maryam Kamgarpour
Control architectures and autonomy stacks for complex engineering systems are often divided into layers to decompose a complex problem and solution into distinct, manageable sub-pr…
Forward-Backward Dynamic Programming for LQG Dynamic Games with Partial and Asymmetric Information
Yuxiang Guan, Iman Shames, Tyler Summers
We formulate and study a class of two-player zero-sum stochastic dynamic games with partial and asymmetric information. Information asymmetry introduces fundamental challenges invo…
Robust Learning-Based Control via Bootstrapped Multiplicative Noise
Benjamin Gravell, Tyler Summers
Despite decades of research and recent progress in adaptive control and reinforcement learning, there remains a fundamental lack of understanding in designing controllers that prov…
Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data
Yu Xing, Ben Gravell, Xingkang He +2
The study of multiplicative noise models has a long history in control theory but is re-emerging in the context of complex networked systems and systems with learning-based control…
Robust Optimal Design of Energy Efficient Series Elastic Actuators: Application to a Powered Prosthetic Ankle
Edgar BolÃvar, Siavash Rezazadeh, Tyler Summers +1
Design of robotic systems that safely and efficiently operate in uncertain operational conditions, such as rehabilitation and physical assistance robots, remains an important chall…
Time-Varying Sensor and Actuator Selection for Uncertain Cyber-Physical Systems
Ahmad F. Taha, Nikolaos Gatsis, Tyler Summers +1
We propose methods to solve time-varying, sensor and actuator (SaA) selection problems for uncertain cyber-physical systems. We show that many SaA selection problems for optimizing…
Augmented Graphs of Convex Sets and the Traveling Salesman Problem
Gael Luna, Tyler Summers
We present a trajectory optimization algorithm for the traveling salesman problem (TSP) in graphs of convex sets (GCS). Our framework uses an augmented graph of convex sets to enco…
Minimisation of Submodular Functions Using Gaussian Zeroth-Order Random Oracles
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +2
We consider the minimisation problem of submodular functions and investigate the application of a zeroth-order method to this problem. The method is based on exploiting a Gaussian…
Robust Data-Driven Output Feedback Control via Bootstrapped Multiplicative Noise
Benjamin Gravell, Iman Shames, Tyler Summers
We propose a robust data-driven output feedback control algorithm that explicitly incorporates inherent finite-sample model estimate uncertainties into the control design. The algo…
Dynamic Programming Through the Lens of Semismooth Newton-Type Methods (Extended Version)
Matilde Gargiani, Andrea Zanelli, Dominic Liao-McPherson +2
Policy iteration and value iteration are at the core of many (approximate) dynamic programming methods. For Markov Decision Processes with finite state and action spaces, we show t…
Actuator Placement under Structural Controllability using Forward and Reverse Greedy Algorithms
Baiwei Guo, Orcun Karaca, Tyler Summers +1
Actuator placement is an active field of research which has received significant attention for its applications in complex dynamical networks. In this paper, we study the problem o…
Simultaneous Sensor and Actuator Selection/Placement through Output Feedback Control
Sebastian Nugroho, Ahmad F. Taha, Tyler Summers +1
In most dynamic networks, it is impractical to measure all of the system states; instead, only a subset of the states are measured through sensors. Consequently, and unlike full st…