Yuichiro Toda

48462098300

Publications - 4

Path planning in probabilistic environment by bacterial memetic algorithm

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2012-12-01

Volume: 14

Issue: Unknown

Page Range: 439-448

Description:

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. In case of probabilistic environment not only static obstacles obstruct the free passage of the robot, but there are appearances of obstacles with probability. The problem is approached by the bacterial memetic algorithm. The objective is to minimize the path length and the number of turns without colliding with an obstacle. Our method is able to generate a collision-free path in probabilistic environment. The proposed algorithm is tested by simulations. © Springer-Verlag Berlin Heidelberg 2012.

Open Access: Yes

DOI: 10.1007/978-3-642-29934-6_42

Bacterial memetic algorithm for simultaneous optimization of path planning and flow shop scheduling problems

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Artificial Life and Robotics

Publication Date: 2012-10-01

Volume: 17

Issue: 1

Page Range: 107-112

Description:

The paper deals with simultaneous optimization of path planning of mobile robots and flow shop scheduling problem. The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. The objective is to minimize the path length without colliding with an obstacle. On the other hand, shop scheduling problems deal with processing a given set of jobs on a given number of machines. Each operation has an associated machine on which it has to be processed for a given length of time. The problem is to minimize the overall time demand of the whole process. In this paper, we deal with two robots carrying items between the machines. Bacterial memetic algorithm is proposed for solving this combined problem. The algorithm is verified by experimental simulations and compared to classical techniques.

Open Access: Yes

DOI: 10.1007/s10015-012-0021-9

Bacterial memetic algorithm for offline path planning of mobile robots

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Memetic Computing

Publication Date: 2012-03-01

Volume: 4

Issue: 1

Page Range: 73-86

Description:

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of combinatorial optimization problems which are approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The objective is to minimize the path length and the number of turns without colliding with an obstacle. The representation used in the paper fits well to the algorithm. Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The method is able to generate a collision-free path for the robot even in complicated search spaces. The proposed algorithm is tested in real environment. © 2012 Springer-Verlag.

Open Access: Yes

DOI: 10.1007/s12293-012-0076-0

Path planning for mobile robots by bacterial memetic algorithm

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: IEEE Ssci 2011 Symposium Series on Computational Intelligence Riiss 2011 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space

Publication Date: 2011-08-12

Volume: Unknown

Issue: Unknown

Page Range: 107-112

Description:

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of hard optimization problems which can be approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The representation used in the paper fits well to the algorithm. Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The proposed algorithm is tested in real environment. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/RIISS.2011.5945787