A game-learning-based smooth path planning strategy for intelligent air-ground vehicle considering mode switching

Author(s):  
Jing Zhao ◽  
Chao Yang ◽  
Weida Wang ◽  
Bin Xu ◽  
Ying Li ◽  
...  
2017 ◽  
Vol 14 (4) ◽  
pp. 297-306 ◽  
Author(s):  
B.B.V.L. Deepak ◽  
M.V.A. Raju Bahubalendruni

Purpose The purpose of this paper is to study the path-planning problem of an unmanned ground vehicle (UGV) in a predefined, structured environment. Design/methodology/approach In this investigation, the environment chosen was the roadmap of the National Institute of Technology, Rourkela, obtained from Google maps as reference. An UGV is developed and programmed so as to move autonomously from an indicated source location to the defined destination in the given map following the most optimal path. Findings An algorithm based on linear search is implemented to the autonomous robot to generate shortest paths in the environment. The developed algorithm is verified with the simulations as well as in experimental environments. Originality/value Unlike the past methodologies, the current investigation deals with the global path-planning strategy as the line following mechanism. Moreover, the proposed technique has been implemented in a real-time environment.


Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 457 ◽  
Author(s):  
JaeHyeon Gwon ◽  
Hyeon Kim ◽  
HyunSoo Bae ◽  
SukGyu Lee

In this paper, we proposed an enhanced path planning strategy for sweeper robots, which were created for the curling Olympic games. The main task for the multi-robot system is to clean the ice surface making a smooth path for a curling stone. The sweeping robots should have a motion planning on how to follow the curling stone slide and to prevent any collisions. In order to find the next position of the sweeping robot, it needs to establish the current position and to compute the next position of the curling stone. The initial and goal points of the sweeping robots are found and set up based on the simulation results from the main server. While the curling stone moves, the sweeping robots measure its position and adjust their motions according to the stone position trajectory. If the distance between the current and the next positions of a curling stone exceeds the threshold value, the sweeping robots should activate the sweeping mechanism preventing collisions with the stone. Since the estimation of the sweeping robot motion solely depends on the stone’s trajectory, the accumulation of errors is undesirable. Thus, the stone trajectory should be recalculated in a certain time step using the trend-adjusted exponential smoothing method. Then, the formation of the sweeping robot system can be calibrated according to the stone path computation. The obtained experimental results proved the efficiency of the proposed path planning method.


Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1821
Author(s):  
Lazaros Moysis ◽  
Karthikeyan Rajagopal ◽  
Aleksandra V. Tutueva ◽  
Christos Volos ◽  
Beteley Teka ◽  
...  

This work proposes a one-dimensional chaotic map with a simple structure and three parameters. The phase portraits, bifurcation diagrams, and Lyapunov exponent diagrams are first plotted to study the dynamical behavior of the map. It is seen that the map exhibits areas of constant chaos with respect to all parameters. This map is then applied to the problem of pseudo-random bit generation using a simple technique to generate four bits per iteration. It is shown that the algorithm passes all statistical NIST and ENT tests, as well as shows low correlation and an acceptable key space. The generated bitstream is applied to the problem of chaotic path planning, for an autonomous robot or generally an unmanned aerial vehicle (UAV) exploring a given 3D area. The aim is to ensure efficient area coverage, while also maintaining an unpredictable motion. Numerical simulations were performed to evaluate the performance of the path planning strategy, and it is shown that the coverage percentage converges exponentially to 100% as the number of iterations increases. The discrete motion is also adapted to a smooth one through the use of B-Spline curves.


Author(s):  
Ho-Hoon Lee

This paper proposes a path planning strategy for high-performance anti-swing control of overhead cranes, where the anti-swing control problem is solved as a kinematic problem. First, two anti-swing control laws, one for hoisting up and the other for hoisting down, are proposed based on the Lyapunov stability theorem. Then a new path-planning strategy is proposed based on the concept of minimum-time control and the proposed anti-swing control laws. The proposed path planning is free from the usual constraints of small load swing, slow hoisting speed, and small hoisting distance. The effectiveness of the proposed path planning is shown by computer simulation with high hoisting speed and hoisting ratio.


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