Predictive haptic guidance: intelligent user assistance for the control of dynamic tasks.
Identifieur interne : 002293 ( PubMed/Checkpoint ); précédent : 002292; suivant : 002294Predictive haptic guidance: intelligent user assistance for the control of dynamic tasks.
Auteurs : Benjamin A C. Forsyth [Canada] ; Karon E. MacleanSource :
- IEEE transactions on visualization and computer graphics [ 1077-2626 ]
English descriptors
- KwdEn :
- Algorithms, Artificial Intelligence, Computer Graphics, Computer Peripherals, Computer Simulation, Computer Systems, Feedback (physiology), Image Enhancement (methods), Image Interpretation, Computer-Assisted (methods), Imaging, Three-Dimensional (methods), Models, Biological, Movement (physiology), Touch (physiology), User-Computer Interface.
- MESH :
Abstract
Intelligent systems are increasingly able to offer real-time information relevant to a user's manual control of an interactive system, such as dynamic system control space constraints for animation control and driving. However, it is difficult to present this information in a usable manner and other approaches which have employed haptic cues for manual control in "slow" systems often lead to instabilities in highly dynamic tasks. We present a predictive haptic guidance method based on a look-ahead algorithm, along with a user evaluation which compares it with other approaches (no guidance and a standard potential-field method) in a 1-DoF steered path-following scenario. Look-ahead guidance outperformed the other methods in both quantitative performance and subjective preference across a range of path complexity and visibility and a force analysis demonstrated that it applied smaller and fewer forces to users. These results (which appear to derive from the predictive guidance's supporting users in taking earlier and more subtle corrective action) suggest the potential of predictive methods in aiding manual control of dynamic interactive tasks where intelligent support is available.
DOI: 10.1109/TVCG.2006.11
PubMed: 16382612
Affiliations:
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However, it is difficult to present this information in a usable manner and other approaches which have employed haptic cues for manual control in "slow" systems often lead to instabilities in highly dynamic tasks. We present a predictive haptic guidance method based on a look-ahead algorithm, along with a user evaluation which compares it with other approaches (no guidance and a standard potential-field method) in a 1-DoF steered path-following scenario. Look-ahead guidance outperformed the other methods in both quantitative performance and subjective preference across a range of path complexity and visibility and a force analysis demonstrated that it applied smaller and fewer forces to users. 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