Collision-free motion planning of multiarm robots using evolutionary algorithms

1997 ◽  
Vol 211 (5) ◽  
pp. 373-384 ◽  
Author(s):  
A S Rana ◽  
A M S Zalzala
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Population Based ◽  
Operational Space ◽  
Planning Algorithm ◽  
Planning Technique ◽  
Pass Through ◽  
Population Based Search ◽  
Path Planning Algorithm ◽  
Path Modification

This paper presents an evolutionary algorithm for the collision-free path planning of multiarm robots. A global path planning technique is used where the paths are represented by a string of via-points that the robots have to pass through, connected together by cubic spline polynomials. Since the entire paths of the robots are considered for optimization, the problem of deadlock between the arms and the static obstacles does not occur. Repeated path modification is done through evolutionary techniques to find an optimized path with respect to length and collision among the robots and the obstacles and the robots themselves. The proposed algorithm departs from simple genetic algorithms in that floating point vector strings represent the chromosomes and customized operators are used to improve upon the performance of the search. Moreover, a local search is carried out on each individual in addition to the global population based search. The result is a highly efficient path-planning algorithm that can deal with complex problems easily. Simulation results are presented for collision-free paths planned for two planar arms and then for two 3 degree-of-freedom (DOF) PUMA®-like arms moving in three-dimensional operational space.

scholarly journals A Path-Planning Strategy for Unmanned Surface Vehicles Based on an Adaptive Hybrid Dynamic Stepsize and Target Attractive Force-RRT Algorithm

2019 ◽  
Vol 7 (5) ◽  
pp. 132 ◽  
Author(s):  
Zhen Zhang ◽  
Defeng Wu ◽  
Jiadong Gu ◽  
Fusheng Li
Keyword(s):  
Path Planning ◽  
High Speed ◽  
Attractive Force ◽  
Simulation Experiments ◽  
Planning Strategy ◽  
Unmanned Surface Vehicles ◽  
Planning Algorithm ◽  
Pass Through ◽  
Path Planning Algorithm ◽  
Narrow Area

It is well known that path planning has always been an important study area for intelligent ships, especially for unmanned surface vehicles (USVs). Therefore, it is necessary to study the path-planning algorithm for USVs. As one of the basic algorithms for USV path planning, the rapidly-exploring random tree (RRT) is popular due to its simple structure, high speed and ease of modification. However, it also has some obvious drawbacks and problems. Designed to perfect defects of the basic RRT and improve the performance of USVs, an enhanced algorithm of path planning is proposed in this study, called the adaptive hybrid dynamic stepsize and target attractive force-RRT(AHDSTAF-RRT). The ability to pass through a narrow area and the forward speed in open areas of USVs are improved by adopting the AHDSTAF-RRT in comparison to the basic RRT algorithm. The improved algorithm is also applied to an actual gulf map for simulation experiments, and the experimental data is collected and organized. Simulation experiments show that the proposed AHDSTAF-RRT in this paper outperforms several existing RRT algorithms, both in terms of path length and calculating speed.

Kinematics of a Novel Single-Loop Under-Actuated Wrist

2012 ◽  
Author(s):  
Raffaele Di Gregorio
Keyword(s):  
Path Planning ◽  
Closed Form ◽  
Nonholonomic Constraint ◽  
Three Dimensional ◽  
Single Loop ◽  
Closed Form Solutions ◽  
Position Analysis ◽  
Tracking Tasks ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A novel type of parallel wrist (PW) is proposed which, differently from previously presented PWs, features a single-loop architecture and only one nonholonomic constraint. Due to the presence of a nonholonomic constraint, the proposed PW type is under-actuated, that is, it is able to control the platform orientation in a three-dimensional workspace by employing only two actuated pairs, one prismatic (P) and the other revolute (R); and it cannot perform tracking tasks. Position analysis and path planning of this novel PW are studied. In particular, all the relevant position analysis problems are solved in closed form, and, based on these closed-form solutions, a path-planning algorithm is built.

scholarly journals Multirobot Formation with Sensor Fusion-Based Localization in Unknown Environment

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1788
Author(s):  
Anh Vu Le ◽  
Koppaka Ganesh Sai Apuroop ◽  
Sriniketh Konduri ◽  
Huy Do ◽  
Mohan Rajesh Elara ◽  
...  
Keyword(s):  
Path Planning ◽  
Sensor Fusion ◽  
Measurement Unit ◽  
Multiple Robots ◽  
Unknown Environment ◽  
Formation Tracking ◽  
Space Experiments ◽  
Planning Algorithm ◽  
Planning Technique ◽  
Path Planning Algorithm

Multirobot cooperation enhancing the efficiency of numerous applications such as maintenance, rescue, inspection in cluttered unknown environments is the interesting topic recently. However, designing a formation strategy for multiple robots which enables the agents to follow the predefined master robot during navigation actions without a prebuilt map is challenging due to the uncertainties of self-localization and motion control. In this paper, we present a multirobot system to form the symmetrical patterns effectively within the unknown environment deployed randomly. To enable self-localization during group formatting, we propose the sensor fusion system leveraging sensor fusion from the ultrawideband-based positioning system, Inertial Measurement Unit orientation system, and wheel encoder to estimate robot locations precisely. Moreover, we propose a global path planning algorithm considering the kinematic of the robot’s action inside the workspace as a metric space. Experiments are conducted on a set of robots called Falcon with a conventional four-wheel skid steering schematic as a case study to validate our proposed path planning technique. The outcome of our trials shows that the proposed approach produces exact robot locations after sensor fusion with the feasible formation tracking of multiple robots system on the simulated and real-world experiments.

scholarly journals A minimum-time obstacle-avoidance path planning algorithm for unmanned aerial vehicles

2021 ◽  
Author(s):  
Arturo De Marinis ◽  
Felice Iavernaro ◽  
Francesca Mazzia
Keyword(s):  
Path Planning ◽  
Minimum Principle ◽  
Three Dimensional ◽  
Planning Problem ◽  
Pontryagin Minimum Principle ◽  
New Strategy ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Vehicle Trajectory ◽  
Path Planning Algorithm

AbstractIn this article, we present a new strategy to determine an unmanned aerial vehicle trajectory that minimizes its flight time in presence of avoidance areas and obstacles. The method combines classical results from optimal control theory, i.e. the Euler-Lagrange Theorem and the Pontryagin Minimum Principle, with a continuation technique that dynamically adapts the solution curve to the presence of obstacles. We initially consider the two-dimensional path planning problem and then move to the three-dimensional one, and include numerical illustrations for both cases to show the efficiency of our approach.

scholarly journals A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 375 ◽  
Author(s):  
Abdul Majeed ◽  
Sungchang Lee
Keyword(s):  
Path Planning ◽  
Computing Time ◽  
Three Dimensional ◽  
Search Space ◽  
Flight Path ◽  
Visibility Graph ◽  
Planning Algorithm ◽  
Path Lengths ◽  
Path Planning Algorithm ◽  
Obstacle Geometry

This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims.

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