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Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/3081

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Subject: search.filters.subject.Motion planning

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    Feedback motion planning with simulation based LQR-trees
    (2021) Chadli, Kouider; Guernane, Reda (supervisor)
    In autonomous and non-autonomous systems, a motion planner generates reference trajectories which are tracked by a low-level controller. In this report we consider the problem of generating a feedback motion planning algorithm for a nonlinear dynamical systems; the algorithm computes the stability regions to build a set of LQR-stabilized trajectories by generating a feedback control law from a set of initial conditions that are goal reachable. Furthermore, we consider the case where these plans must be generated offline, because the LQR trees lack the ability to handle events in which the goal and environments are unknown till run-time. Moreover, the algorithm approximates the funnel [2] of a trajectory using the one step Lyapunov method which is a sampling-based approach, generating a control law that stabilizes the bounded set to the goal is equivalent to adding trajectories to the tree until their funnels cover the design set. We further validate our approach by carefully evaluating the guarantees on invariance provided by funnels on nonlinear systems. We demonstrate and validate our method using simulation experiments of some nonlinear models. These demonstrations constitute examples of provably safe and robust control for robotic systems with complex nonlinear dynamics with Obstacles and dynamic constraints.
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    Feedback motion planning for teyhered mobile robots
    (2021) Hambli, Billel; Charef, Redha; Guernane, Reda (supervisor)
    In this report titled Feedback motion planning for tethered mobile robots, we employ many concepts in order to arrive at a methodology by which path planning of tethered robots can be achieved using feedback. These concepts include constructing a map of the encountered homotopic classes in our environment, building an augmented and tether aware virtual potential field that is responsible for both the advancement towards the goal and the retraction to the anchor of the tether, and the use of path shortening and length calculation algorithms. For the purpose of simplicity, our approach is only limited to the cases where there is no tether crossing while being wrapped around an obstacle. A discrete implementation of the suggested strategy using wavefront planner is presented as a proof of concept.
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    Motion planning for a tethered mobile robot
    (2019) Ammour, Manel; Guernane, Rida (supervisor)
    Recently there has been surge of research in motion planning for tethered robots. In this problem a planar robot is connected to a base via a flexible cable assumed to be always stretched of limited length L. The existence of the cable causes additional constraints on the motion of the robot. Our method consists of finding a shortest path for a robot having an initial cable layout from a given position to the goal. The shortcut algorithm is used to estimate the cable configuration by smoothing and refining the path constituted of the concatenation of the initial cable layout and the path candidate without violating the homotopy class. This heuristic determines whether a target position can be reached for a given tether configuration. The algorithm was evaluated and validated on Matlab by planning trajectories in an environment with obstacles of different shapes, and by setting different cable lengths. The results of our path planning approach have shown that the obtained smoothed path between base and goal position matches exactly the cable’s configuration. In addition, homotopy classes are preserved when performing the smoothing operation over the path.