TY - GEN
T1 - Recognition, prediction, and planning for assisted teleoperation of freeform tasks
AU - Hauser, Kris
N1 - Publisher Copyright:
© 2013 Massachusetts Institute of Technology.
PY - 2013
Y1 - 2013
N2 - This paper presents a system for improving the intuitiveness and responsiveness of assisted robot teleoperation interfaces by combining intent prediction and motion planning. Two technical contributions are described. First, an intent predictor estimates the user's desired task, and accepts freeform tasks that include both discrete types and continuous parameters (e.g., desired target positions). Second, a cooperative motion planner uses the task estimates to generate continuously updated robot trajectories by solving optimal control problems with timevarying objective functions. The planner is designed to respond interactively to changes in the indicated task, avoid collisions in cluttered environments, and achieve high-quality motions using a hybrid of numerical and sample-based techniques. The system is applied to the problem of controlling a 6D robot manipulator using 2D mouse input in the context of two tasks: static target reaching and dynamic trajectory tracking. Simulations suggest that it enables the robot to reach static targets faster and to track trajectories more closely than comparable techniques.
AB - This paper presents a system for improving the intuitiveness and responsiveness of assisted robot teleoperation interfaces by combining intent prediction and motion planning. Two technical contributions are described. First, an intent predictor estimates the user's desired task, and accepts freeform tasks that include both discrete types and continuous parameters (e.g., desired target positions). Second, a cooperative motion planner uses the task estimates to generate continuously updated robot trajectories by solving optimal control problems with timevarying objective functions. The planner is designed to respond interactively to changes in the indicated task, avoid collisions in cluttered environments, and achieve high-quality motions using a hybrid of numerical and sample-based techniques. The system is applied to the problem of controlling a 6D robot manipulator using 2D mouse input in the context of two tasks: static target reaching and dynamic trajectory tracking. Simulations suggest that it enables the robot to reach static targets faster and to track trajectories more closely than comparable techniques.
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U2 - 10.15607/rss.2012.viii.016
DO - 10.15607/rss.2012.viii.016
M3 - Conference contribution
AN - SCOPUS:84959261923
SN - 9780262519687
T3 - Robotics: Science and Systems
SP - 121
EP - 128
BT - Robotics
A2 - Newman, Paul
A2 - Roy, Nicholas
A2 - Srinivasa, Siddhartha
PB - MIT Press Journals
T2 - International Conference on Robotics Science and Systems, RSS 2012
Y2 - 9 July 2012 through 13 July 2012
ER -