Dynamically feasible task-constrained motion planning with moving obstacles
We present a randomized algorithm for planning dynamically feasible motions of robots subject to geometric task constraints in the presence of moving obstacles. The proposed method builds upon our previous results on task-constrained motion planning with moving obstacles. With respect to our previou...
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          | Published in | Proceedings - IEEE International Conference on Robotics and Automation pp. 2045 - 2050 | 
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| Main Authors | , | 
| Format | Conference Proceeding | 
| Language | English | 
| Published | 
            IEEE
    
        01.05.2014
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 1050-4729 | 
| DOI | 10.1109/ICRA.2014.6907130 | 
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| Abstract | We present a randomized algorithm for planning dynamically feasible motions of robots subject to geometric task constraints in the presence of moving obstacles. The proposed method builds upon our previous results on task-constrained motion planning with moving obstacles. With respect to our previous formulation, the inclusion of bounds on the available actuator torques leads to the adoption of an acceleration-level motion generation scheme. Therefore, the new planner must operate in a task-constrained state space extended with time. The generated trajectories are collision-free, obey velocity and torque bounds, and satisfy the task constraint with arbitrary accuracy. The effectiveness of the proposed approach is shown by results on various scenarios involving a 7-dof manipulator. | 
    
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| AbstractList | We present a randomized algorithm for planning dynamically feasible motions of robots subject to geometric task constraints in the presence of moving obstacles. The proposed method builds upon our previous results on task-constrained motion planning with moving obstacles. With respect to our previous formulation, the inclusion of bounds on the available actuator torques leads to the adoption of an acceleration-level motion generation scheme. Therefore, the new planner must operate in a task-constrained state space extended with time. The generated trajectories are collision-free, obey velocity and torque bounds, and satisfy the task constraint with arbitrary accuracy. The effectiveness of the proposed approach is shown by results on various scenarios involving a 7-dof manipulator. | 
    
| Author | Oriolo, Giuseppe Cefalo, Massimo  | 
    
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| SubjectTerms | Acceleration Joints Kinematics Manipulators Planning Torque  | 
    
| Title | Dynamically feasible task-constrained motion planning with moving obstacles | 
    
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