32 citations · 95 across the 14 of their papers we have counts for
14 papers
Dynamic distributed decision-making for resilient resource reallocation in disrupted manufacturing systems
Mingjie Bi, Ilya Kovalenko, Dawn M. Tilbury +1
The COVID-19 pandemic brings many unexpected disruptions, such as frequently shifting markets and limited human workforce, to manufacturers. To stay competitive, flexible and real-…
A Multi-objective Mixed-integer Programming Approach for Supply Chain Disruption Response with Lead-Time Awareness
Juan-Alberto Estrada-Garcia, Mingjie Bi, Dawn M. Tilbury +2
Supply chain (SC) risk management is influenced by both spatial and temporal attributes of different entities (suppliers, retailers, and customers). Each entity has given capacity…
Opportunities and Challenges to Integrate Artificial Intelligence into Manufacturing Systems: Thoughts from a Panel Discussion
Ilya Kovalenko, Kira Barton, James Moyne +1
Rapid advances in artificial intelligence (AI) have the potential to significantly increase the productivity, quality, and profitability in future manufacturing systems. Traditiona…
Learning Task Requirements and Agent Capabilities for Multi-agent Task Allocation
Bo Fu, William Smith, Denise Rizzo +3
This paper presents a learning framework to estimate an agent capability and task requirement model for multi-agent task allocation. With a set of team configurations and the corre…
A Model-based Multi-agent Framework to Enable an Agile Response to Supply Chain Disruptions
Mingjie Bi, Gongyu Chen, Dawn M. Tilbury +2
Due to the COVID-19 pandemic, the global supply chain is disrupted at an unprecedented scale under uncertain and unknown trends of labor shortage, high material prices, and changin…
Simultaneous Human-robot Matching and Routing for Multi-robot Tour Guiding under Time Uncertainty
Bo Fu, Tribhi Kathuria, Denise Rizzo +4
This work presents a framework for multi-robot tour guidance in a partially known environment with uncertainty, such as a museum. In the proposed centralized multi-robot planner, a…
Merging Subject Matter Expertise and Deep Convolutional Neural Network for State-Based Online Machine-Part Interaction Classification
Hao Wang, Yassine Qamsane, James Moyne +1
Machine-part interaction classification is a key capability required by Cyber-Physical Systems (CPS), a pivotal enabler of Smart Manufacturing (SM). While previous relevant studies…
Learning-Based Repetitive Precision Motion Control with Mismatch Compensation
Efe C. Balta, Kira Barton, Dawn M. Tilbury +2
Learning-based control methods utilize run-time data from the underlying process to improve the controller performance under model mismatch and unmodeled disturbances. This is bene…
Iterative learning control with discrete-time nonlinear nonminimum phase models via stable inversion
Isaac A Spiegel, Nard Strijbosch, Tom Oomen +1
Output reference tracking can be improved by iteratively learning from past data to inform the design of feedforward control inputs for subsequent tracking attempts. This process i…
Receding Horizon Iterative Learning Control for Continuously Operated Systems
Maxwell Wu, Mitchell Cobb, James Reed +3
This paper presents an iterative learning control (ILC) scheme for continuously operated repetitive systems for which no initial condition reset exists. To accomplish this, we deve…
Dynamic Semantic Occupancy Mapping using 3D Scene Flow and Closed-Form Bayesian Inference
Aishwarya Unnikrishnan, Joey Wilson, Lu Gan +4
This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. Existence of dynamic objects in…
Robust Task Scheduling for Heterogeneous Robot Teams under Capability Uncertainty
Bo Fu, William Smith, Denise Rizzo +3
This paper develops a stochastic programming framework for multi-agent systems where task decomposition, assignment, and scheduling problems are simultaneously optimized. The frame…
Heterogeneous Vehicle Routing and Teaming with Gaussian Distributed Energy Uncertainty
Bo Fu, William Smith, Denise Rizzo +2
For robot swarms operating on complex missions in an uncertain environment, it is important that the decision-making algorithm considers both heterogeneity and uncertainty. This pa…
Exponential Stability of Nonlinear Differential Repetitive Processes with Applications to Iterative Learning Control
Berk Altın, Kira Barton
This paper studies exponential stability properties of a class of two-dimensional (2D) systems called differential repetitive processes (DRPs). Since a distinguishing feature of DR…