Object Conveyance Algorithm for Multiple Mobile Robots based on Object Shape and Size

This paper describes a determination method of a number of a team for multiple mobile robot object conveyance. The number of robot on multiple mobile robot systems is the factor of complexity on robots formation and motion control. In our previous research, we verified the use of the complex-valued neural network for controlling multiple mobile robots in object conveyance problem. Though it is a significant issue to develop effective determination team member for multiple mobile robot object conveyance, few studies have been done on it. Therefore, we propose an algorithm for determining the number of the team member on multiple mobile robot object conveyance with grasping push. The team member is determined based on object weight to obtain appropriate formation. First, the object shape and size measurement is carried out by a surveyor robot that approaches and surrounds the object. During surrounding the object, the surveyor robot measures its distance to the object and records for estimating the object shape and size. Since the object shape and size are estimated, the surveyor robot makes initial push position on the estimated push point and calls additional robots for cooperative push. The algorithm is validated in several computer simulations with varying object shape and size. As a result, the proposed algorithm is promising for minimizing the number of the robot on multiple mobile robot object conveyance.

@article{Sejati2016,
  title     = {Object Conveyance Algorithm for Multiple Mobile Robots based on Object Shape and Size},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {5},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Purnomo Sejati and Hiroshi Suzuki and Takahiro Kitajima and Akinobu Kuwahara and Takashi Yasuno},
  doi       = {10.14569/IJACSA.2016.070573},
  url       = {https://doi.org/10.14569/IJACSA.2016.070573}
}