X Vision: a portable substrate for real-time vision applications
Computer Vision and Image Understanding
A Sensor-based Telerobotic System for the Space Robot Experiment ROTEX
The 2nd International Symposium on Experimental Robotics II
Performance of Robotic Augmentation in Microsurgery-Scale Motions
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Fusion of Human and Machine Intelligence for Telerobotic Systems
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
HAPTICS '02 Proceedings of the 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
Recognition of Operator Motions for Real-Time Assistance Using Virtual Fixtures
HAPTICS '03 Proceedings of the 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (HAPTICS'03)
Vision-assisted control for manipulation using virtual fixtures
IEEE Transactions on Robotics
International Journal of Robotics Research
Motion intention recognition in robot assisted applications
Robotics and Autonomous Systems
Incremental Learning and Memory Consolidation of Whole Body Human Motion Primitives
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Position-correcting tools for 2D digital fabrication
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Robotics and Computer-Integrated Manufacturing
A policy-blending formalism for shared control
International Journal of Robotics Research
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Human-machine collaborative systems (HMCSs) are systems that amplify or assist human capabilities during the performance of tasks that require both human judgment and robotic precision. We examine the design and performance of HMCSs in the context of microsurgical procedures such as vitreo-retinal eye surgery. Three specific problems considered are: (1) development of systems tools for describing and implementing HMCSs, (2) segmentation of complex tasks into logical components given sensor traces of human task execution, and (3) measurement and evaluation of HMCS performance. These components can be integrated into a complete workstation with the ability to automatically "parse" traces of user activities into task models, which are loaded into an execution environment to provide the user with assistance using on-line recognition of task states. The major contributions of this work include an XML task graph modeling framework and execution engine, an algorithm for real-time segmentation of user actions using continuous hidden Markov models, and validation techniques for analyzing the performance of HMCSs.