Avoiding local minima in the potential field method using input-to-state stability

Guerra, Gabriel M.; Efimov, Denis; Zheng, Gang; Perruquetti, Wilfrid

doi:10.1016/j.conengprac.2016.07.008

Cited by 40 publications

(18 citation statements)

References 38 publications

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“…A challenge for each of these algorithms is the local minima trap issue, which draws much attention from researchers. 7–9 To generate dynamically feasible paths, the latest APF methods, 10,11 integrated with the model predictive control (MPC) methods, take into account the vehicle dynamics. The APF methods can generate safe vehicle motions online, and hence are suitable for real-time applications.…”

Section: Related Workmentioning

confidence: 99%

Two-phase A*: A real-time global motion planning method for non-holonomic unmanned ground vehicles

Zhang

Yang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a search-based global motion planning method, called the two-phase A*, with an adaptive heuristic weight. This method is suitable for planning a global path in real time for a car-like vehicle in both indoor and outdoor environments. In each planning cycle, the method first estimates a proper heuristic weight based on the hardness of the planning query. Then, it finds a nearly optimal path subject to the non-holonomic constraints using an improved A* with a weighted heuristic function. By estimating the heuristic weight dynamically, the two-phase A* is able to adjust the optimality level of its path based on the hardness of the planning query. Therefore, the two-phase A* sacrifices little planning optimality, and its computation time is acceptable in most situations. The two-phase A* has been implemented and tested in the simulations and real-world experiments over various task environments. The results show that the two-phase A* can generate a nearly optimal global path dynamically, which satisfies the non-holonomic constraints of a car-like vehicle and reduces the total navigation time.

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Section: Related Workmentioning

confidence: 99%

Two-phase A*: A real-time global motion planning method for non-holonomic unmanned ground vehicles

Zhang

Yang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…This subsection presents an approach to transform the under-actuated system, via a coordinate transformation [48],to a simpler one for controller design. Considering the dynamics of a point Q on the X b -axis of the blimp body-fixed frame (see Fig.…”

Section: Transformationmentioning

confidence: 99%

Disturbance compensation based controller for an indoor blimp robot

Wang

Zheng

Efimov

et al. 2020

Robotics and Autonomous Systems

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This paper presents the robust controller design for an indoor blimp robot to achieve application such as the surveillance. The commonly used 6 degrees of freedom dynamic model is simplified under reasonable assumptions and decoupled into two independent parts. The blimp simplified horizontal plane movement model is complemented with disturbance terms to ensure the modeling accuracy, then it is transformed to a simpler form for the ease of controller design. Next, the disturbance terms are evaluated by the designed real-time estimator, and the perturbation estimates are compensated in the conceived motion controller for cancellation of the influence of disturbances. The performance and robustness of the disturbance compensation-based controller are verified by both simulations and experiments on the developed blimp robot. Finally, the results prove the feasibility of the blimp robot in indoor surveillance application by stabilizing itself at a fixed position or patrolling along a predefined path.

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“…Several efforts have been made by researchers to address the path planning problem for robots docking already [13,15,[20][21][22][23][24][25][26][27]. Among them, one of the most popular approaches is the artificial potential field (APF) method.…”

Section: Introductionmentioning

confidence: 99%

“…With properly designed potential functions, the robot will be navigated to the goal point and avoid collision in real time. However, the local minimal points of the total potential field in the navigation process may cause the local minima problem of the APF method which will prevent the robot from approaching the destination [24]. In [22], the APF approach is adopted to generate the desired trajectory for an AUV homing and docking.…”

Section: Introductionmentioning

confidence: 99%

Smooth Path Planning for Robot Docking in Unknown Environment with Obstacles

et al. 2018

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This paper presents an integrated approach to plan smooth path for robots docking in unknown environments with obstacles. To determine the smooth collision-free path in obstacle environment, a tree structure with heuristic expanding strategy is designed as the foundation of path planning in this approach. The tree employs 3D Dubins curves as its branches and foundation for path feasibility evaluation. For the efficiency of the tree expanding in obstacle environment, intermediate nodes and collision-free branches are determined inspired by the elastic band theory. A feasible path is chosen as the shortest series of branches that connects to the docking station after the sufficient expansion of the tree. Simulation results are presented to show the validity and feasibility of the proposed approach.

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Avoiding local minima in the potential field method using input-to-state stability

Cited by 40 publications

References 38 publications

Two-phase A*: A real-time global motion planning method for non-holonomic unmanned ground vehicles

Two-phase A*: A real-time global motion planning method for non-holonomic unmanned ground vehicles

Disturbance compensation based controller for an indoor blimp robot

Smooth Path Planning for Robot Docking in Unknown Environment with Obstacles

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