Task-priority based redundancy control of robot manipulators
International Journal of Robotics Research
Robot Control: The Task Function Approach
Robot Control: The Task Function Approach
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
An inverse kinematics architecture enforcing an arbitrary number of strict priority levels
The Visual Computer: International Journal of Computer Graphics - Special section on implicit surfaces
Planning Algorithms
Reactive path deformation for nonholonomic mobile robots
IEEE Transactions on Robotics
Newton-Type Algorithms for Dynamics-Based Robot Movement Optimization
IEEE Transactions on Robotics
Task Sequencing for High-Level Sensor-Based Control
IEEE Transactions on Robotics
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This paper presents a method for sequencing a set of robotic tasks in an optimal way. Tasks description and execution are based on the task-function approach, which enables to build complex whole-body behaviors from local control laws. A naive solution to this problem would be to schedule the execution of the tasks sequentially, avoiding concurrency. This solution does not exploit full robot capabilities such as redundancy and have poor performance in terms of execution time or energy. However, reasoning on concurrent tasks is difficult while accounting for all the physical constraints of the robot. Our contribution is to determine the time-optimal realization of the mission taking into account robotic constraints that may be as complex as collision avoidance. Our approach achieves more than a simple scheduling; its originality lies in maintaining the task approach in the formulated optimization of the task sequencing problem. This theory is exemplified through a complete experiment on the real HRP-2 robot.