A Spherical Hierarchical Representation for Robot Motion Planning

1991 ◽  
Author(s):  
Angel Pasqual del Pobil ◽  
Miguel A. Serna
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Free Path ◽  
Collision Detection ◽  
Spherical Model ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Simple Treatment ◽  
Practical Model ◽  
Solid Bodies

Abstract A simple and practical model with applications in 3D motion planning is presented. The new model is based on a double spherical hierarchy of detail to represent solid bodies. First, each element making up the robot and the obstacles is approximated by means of a set of exterior spheres which are automatically defined. Second, another set composed of interior spheres is generated. These representations define a hierarchy, since they can be redefined as many times as necessary: starting with two spheres per element, the approximation may be improved until it contains hundreds of spheres. Moreover, they converge to a zero-error representation. The proposed spherical model leads to a simple treatment for the problem of dynamic collision detection, and it is further applied to collision-free path planning for robot manipulators in 3D.

scholarly journals Advanced algorithms for mobile robot motion planning and tracking in structured static environments using particle swarm optimization

2012 ◽  
Vol 9 (1) ◽  
pp. 9-28 ◽  
Author(s):  
Aleksandar Cosic ◽  
Marko Susic ◽  
Dusko Katic
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Planning ◽  
Free Path ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Complex Problem ◽  
Pi Controller ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Swarm Optimization

An approach to intelligent robot motion planning and tracking in known and static environments is presented in this paper. This complex problem is divided into several simpler problems. The first is generation of a collision free path from starting to destination point, which is solved using a particle swarm optimization (PSO) algorithm. The second is interpolation of the obtained collision-free path, which is solved using a radial basis function neural network (RBFNN), and trajectory generation, based on the interpolated path. The last is a trajectory tracking problem, which is solved using a proportional-integral (PI) controller. Due to uncertainties, obstacle avoidance is still not ensured, so an additional fuzzy controller is introduced, which corrects the control action of the PI controller. The proposed solution can be used even in dynamic environments, where obstacles change their position in time. Simulation studies were realized to validate and illustrate this approach.

scholarly journals Motion Planning for Mobile Robot with Modified BIT* and MPC

2021 ◽  
Vol 11 (1) ◽  
pp. 426
Author(s):  
Puyong Xu ◽  
Ning Wang ◽  
Shi-Lu Dai ◽  
Lei Zuo
Keyword(s):  
Model Predictive Control ◽  
Mobile Robot ◽  
Motion Planning ◽  
Objective Function ◽  
Free Path ◽  
Predictive Control ◽  
Planning Method ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Simulation Results

In this paper, a mobile robot motion planning method with modified BIT* (batch informed trees) and MPC (Model Predictive Control) is presented. The conventional BIT* was modified here by integrating a stretch method that improves the path points connections, to get a collision-free path more quickly. After getting a reference path, the MPC method is employed to determine the motion at each moment with a given objective function. In the objective function, a repulsive function based on the direction and distance of the obstacles is introduced to avoid the robot being too close to the obstacle, so the safety can be ensured. Simulation results show the good navigation performance of the whole framework in different scenarios.

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