Path Planning of Lunar Robot Based on an Adaptive Ant Colony Algorithm
W Zhu, S Zhu, X Zhang, T Cao - … of the 5th International Conference on …, 2019 - dl.acm.org
Path planning of lunar robots is the guarantee that lunar robots can complete tasks safely
and accurately. Aiming at the shortest path and the least energy consumption, an adaptive
potential field ant colony algorithm (A-APFACO) suitable for path planning of lunar robot was
proposed to solve the problems of slow convergence speed and easy to fall into local
optimum of ant colony algorithm. This algorithm combines the artificial potential field method
with ant colony algorithm, introduces the inducement heuristic factor, and adjusts the state …
and accurately. Aiming at the shortest path and the least energy consumption, an adaptive
potential field ant colony algorithm (A-APFACO) suitable for path planning of lunar robot was
proposed to solve the problems of slow convergence speed and easy to fall into local
optimum of ant colony algorithm. This algorithm combines the artificial potential field method
with ant colony algorithm, introduces the inducement heuristic factor, and adjusts the state …
Path planning of lunar robot based on dynamic adaptive ant colony algorithm and obstacle avoidance
S Zhu, W Zhu, X Zhang, T Cao - International Journal of …, 2020 - journals.sagepub.com
Path planning of lunar robots is the guarantee that lunar robots can complete tasks safely
and accurately. Aiming at the shortest path and the least energy consumption, an adaptive
potential field ant colony algorithm suitable for path planning of lunar robot is proposed to
solve the problems of slow convergence speed and easy to fall into local optimum of ant
colony algorithm. This algorithm combines the artificial potential field method with ant colony
algorithm, introduces the inducement heuristic factor, and adjusts the state transition rule of …
and accurately. Aiming at the shortest path and the least energy consumption, an adaptive
potential field ant colony algorithm suitable for path planning of lunar robot is proposed to
solve the problems of slow convergence speed and easy to fall into local optimum of ant
colony algorithm. This algorithm combines the artificial potential field method with ant colony
algorithm, introduces the inducement heuristic factor, and adjusts the state transition rule of …
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