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Layered task planning for mobile manipulators
(Elsevier, 2019) Djezairi, Salim; Boushaki Zamoum, Razika; Akli, Isma; Bouzouia, Brahim
Task planning for mobile manipulators is a challenging problem in robotics. Mobile ma- nipulators can perform a wide range of tasks in complex environments. They must process the symbolic knowledge in order to find a sequence of actions that achieves the specified goals. This paper proposes a hybrid approach named Planning with Shortcuts. It uses a data structure called Layered Task Graph (LTG) which groups primitive actions, robot skills and task patterns in a strictly hierarchical manner. It then uses the LTG to create shortcuts in the state space in order to accelerate the search. A task planner is called to find a set of actions that achieves the goal task. The result of the search is a sequence of high level actions and primitive actions. The high level actions are then decomposed using the task decomposition approach.
Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control
(Elsevier, 2017) Bakdi, Azzeddine; Hentout, Abdelfetah; Boutami, Hakim; Maoudj, Abderraouf; Hachour, Ouarda; Bouzouia, Brahim