A suboptimal and analytical solution to mobile robot trajectory generation amidst moving obstacles

Peng, Jun; Luo, Wenhao; Liu, Weirong; Yu, Wentao; Wang, Jing

doi:10.1007/s10514-015-9424-5

Cited by 12 publications

(4 citation statements)

References 42 publications

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“…However, sometimes only local knowledge about the environment can be obtained in practice while the replanning process could not be implemented in advance [36][37][38][39]. Moreover, if the area for docking is crowded with obstacles, the efficiency of the path replanning process is critical.…”

Section: Path Replanning Strategymentioning

confidence: 99%

Reactive Path Planning Approach for Docking Robots in Unknown Environment

Cui

Yan

Wang

2017

Journal of Advanced Transportation

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Autonomous robots need to be recharged and exchange information with the host through docking in the long-distance tasks. Therefore, feasible path is required in the docking process to guide the robot and adjust its pose. However, when there are unknown obstacles in the work area, it becomes difficult to determine the feasible path for docking. This paper presents a reactive path planning approach named Dubins-APF (DAPF) to solve the path planning problem for docking in unknown environment with obstacles. In this proposed approach the Dubins curves are combined with the designed obstacle avoidance potential field to plan the feasible path. Firstly, an initial path is planned and followed according to the configurations of the robot and the docking station. Then when the followed path is evaluated to be infeasible, the intermediate configuration is calculated as well as the replanned path based on the obstacle avoidance potential field. The robot will be navigated to the docking station with proper pose eventually via the DAPF approach. The proposed DAPF approach is efficient and does not require the prior knowledge about the environment. Simulation results are given to validate the effectiveness and feasibility of the proposed approach.

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Section: Path Replanning Strategymentioning

confidence: 99%

Reactive Path Planning Approach for Docking Robots in Unknown Environment

Cui

Yan

Wang

2017

Journal of Advanced Transportation

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“…These uses introduce the need for nonholonomic restrictions when the robot is modelled, and in many cases this raises the issue of obtaining the trajectory as an optimization problem, as in Peng et al [3]. In the case of autonomous vehicles, there are specific problems associated with driving on different road types (see Katrakazas et al [4]).…”

Section: Introductionmentioning

confidence: 99%

Influence of the Friction Coefficient on the Trajectory Performance for a Car‐Like Robot

Valero

Rubio

Llopis-Albert

et al. 2017

Mathematical Problems in Engineering

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A collision-free trajectory planner for a car-like mobile robot moving in complex environments is introduced and the influence of the coefficient of friction on important working parameters is analyzed. The proposed planner takes into account not only the dynamic capabilities of the robot but also the behaviour of the tire. This planner is based on sequential quadratic programming algorithms and the normalized time method. Different values for the coefficient of friction have been taken following a normal Gaussian distribution to see its influence on the working parameters. The algorithm has been applied to several examples and the results show that computation times are compatible with real-time work, so the authors call them efficient generated trajectories as they avoid collisions. Besides, working parameters such as the minimum trajectory time, the maximum vehicle speed, computational time, and consumed energy have been monitored and some conclusions have been reached.

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“…Sensing and Avoidance (S&A) is a major pattern for threat avoidance. The aircraft's collision avoidance methods can be divided into the following categories: (1) the method of resolving the guidance law based on geometrical relationships [6][7][8]. This method calculates the guidance law of avoidance manoeuvre according to the relative distance, speed, acceleration, angle, etc., between the aircraft and threats, but it is difficult to apply in complex threat airspace.…”

Section: Introductionmentioning

confidence: 99%

UAV autonomous collision avoidance approach

Wei

Zhang

2017

Automatika

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The conventional sense-and-avoid collision avoidance mode of UAV (unmaned aerial vehicle) lacks applicability and timeliness in a multi-threat environment. In this paper, a new efficient collision avoidance approach for uncertain threat environments derived from the idea of autonomous mental development is proposed. The proposed collision avoidance pattern consists of a sensory layer, a logic layer and a development layer. The threat information is sensed using the sensory layer, and the path planning approach in the logical layer is applied to the output configuration of UAV. In the development phase, the developmental networks approach is used for online learning, training and updating the logical layer so as to form the sense-action mapping, which is stored as the "basic experience" for UAV executing the avoidance manoeuvre. In the implementation phase, the command is executed by matching the sensing information and action base. The simulation results show that the proposed approach has better timeliness compared to the conventional approaches.

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A suboptimal and analytical solution to mobile robot trajectory generation amidst moving obstacles

Cited by 12 publications

References 42 publications

Reactive Path Planning Approach for Docking Robots in Unknown Environment

Reactive Path Planning Approach for Docking Robots in Unknown Environment

Influence of the Friction Coefficient on the Trajectory Performance for a Car‐Like Robot

UAV autonomous collision avoidance approach

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