8 citations · 18 across the 10 of their papers we have counts for
10 papers
Adaptive Obstacle-Aware Task Assignment and Planning for Heterogeneous Robot Teaming
Nan Li, Jiming Ren, Haris Miller +3
Multi-Agent Task Assignment and Planning (MATP) has attracted growing attention but remains challenging in terms of scalability, spatial reasoning, and adaptability in obstacle-ric…
Accelerating Signal-Temporal-Logic-Based Task and Motion Planning of Bipedal Navigation using Benders Decomposition
Jiming Ren, Xuan Lin, Roman Mineyev +3
Task and motion planning under Signal Temporal Logic constraints is known to be NP-hard. A common class of approaches formulates these hybrid problems, which involve discrete task…
Aligning Judgment Using Task Context and Explanations to Improve Human-Recommender System Performance
Divya Srivastava, Karen M. Feigh
Recommender systems, while a powerful decision making tool, are often operationalized as black box models, such that their AI algorithms are not accessible or interpretable by huma…
LTL-D*: Incrementally Optimal Replanning for Feasible and Infeasible Tasks in Linear Temporal Logic Specifications
Jiming Ren, Haris Miller, Karen M. Feigh +2
This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-based task planning in a dynamically changing environment. Unexpected changes in the envi…
Inferring Belief States in Partially-Observable Human-Robot Teams
Jack Kolb, Karen M. Feigh
We investigate the real-time estimation of human situation awareness using observations from a robot teammate with limited visibility. In human factors and human-autonomy teaming,…
Improving Operator Situation Awareness when Working with AI Recommender Systems
Divya K. Srivastava, J. Mason Lilly, Karen M. Feigh
AI recommender systems are sought for decision support by providing suggestions to operators responsible for making final decisions. However, these systems are typically considered…
Converging Measures and an Emergent Model: A Meta-Analysis of Human-Automation Trust Questionnaires
Yosef S. Razin, Karen M. Feigh
A significant challenge to measuring human-automation trust is the amount of construct proliferation, models, and questionnaires with highly variable validation. However, all agree…
Committing to Interdependence: Implications from Game Theory for Human-Robot Trust
Yosef S. Razin, Karen M. Feigh
Human-robot interaction and game theory have developed distinct theories of trust for over three decades in relative isolation from one another. Human-robot interaction has focused…
Effects of Interruptibility-Aware Robot Behavior
Siddhartha Banerjee, Andrew Silva, Karen Feigh +1
As robots become increasingly prevalent in human environments, there will inevitably be times when a robot needs to interrupt a human to initiate an interaction. Our work introduce…
ATC Taskload Inherent to the Geometry of Stochastic 4-D Trajectory Flows with Flight Technical Errors
Vlad Popescu, John-Paul B. Clarke, Karen M. Feigh +1
A method to quantify the probabilistic controller taskload inherent to maintaining aircraft adherence to 4-D trajectories within flow corridors is presented. An Ornstein-Uhlenbeck…