An Opportunistic Strategy for Motion Planning in the Presence of Soft Task Constraints
| Autor: | Paolo Ferrari, Massimo Cefalo, Giuseppe Oriolo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Control and Optimization Computer science Biomedical Engineering 02 engineering and technology Kinematics redundant robots Task (project management) 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Motion planning collision avoidance Robot kinematics motion and path planning Mobile manipulator Mechanical Engineering 020208 electrical & electronic engineering soft tasks Collision Computer Science Applications Human-Computer Interaction Control and Systems Engineering Path (graph theory) Task analysis Robot Computer Vision and Pattern Recognition Configuration space |
| Popis: | Consider the problem of planning collision-free motions for a robot that is assigned a soft task constraint, i.e., a desired path in task space with an associated error tolerance. To this end, we propose an opportunistic planning strategy in which two subplanners take turns in generating motions. The hard planner guarantees exact realization of the desired task path until an obstruction is detected in configuration space; at this point, it invokes the soft planner , which is in charge of exploiting the available task tolerance to bypass the obstruction and returning control to the hard planner as soon as possible. As a result, the robot will perform the desired task for as long as possible, and deviate from it only when strictly needed to avoid a collision. We present several planning experiments performed in V-REP for the PR2 mobile manipulator in order to show the effectiveness of the proposed planner. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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