PF-CD3Q uses online particle filtering to estimate fatigue parameters and constrains a deep Q-learning agent to solve fatigue-aware human-robot task planning as a CMDP.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 2roles
background 2polarities
background 2representative citing papers
A combined SHARD and STPA hazard analysis of a mammography support robot reveals interaction-based risks and translates them into safety constraints that reduce dependence on perfect human timing.
citing papers explorer
-
Safe reinforcement learning with online filtering for fatigue-predictive human-robot task planning and allocation in production
PF-CD3Q uses online particle filtering to estimate fatigue parameters and constrains a deep Q-learning agent to solve fatigue-aware human-robot task planning as a CMDP.
-
Hazard Management in Robot-Assisted Mammography Support
A combined SHARD and STPA hazard analysis of a mammography support robot reveals interaction-based risks and translates them into safety constraints that reduce dependence on perfect human timing.