Taro Nakamura and Kuniaki Satoh
The snail moves by propagating traveling waves from tail to head. If it is possible to propagate a traveling wave in many directions, an omni‐directional mobile robot could be…
Abstract
Purpose
The snail moves by propagating traveling waves from tail to head. If it is possible to propagate a traveling wave in many directions, an omni‐directional mobile robot could be realized. The purpose of this paper is to develop an omni‐directional mobile robot using the locomotion mechanism of the snail and to study the basic properties of the robot.
Design/methodology/approach
A unit for mobile robot was developed to generate the traveling wave based on the snail. The omni‐directional mobile robot is composed of eight units arranged in a circular shape and each abutting unit is connected by a spring. The robot generates a traveling wave by elongation and contraction of the units and realizes an omni‐directional locomotion.
Findings
It was confirmed that the robot moves using the traveling wave locomotion. Furthermore, the locomotion experiment confirmed that the robot moved in the expected direction with reasonable accuracy.
Originality/value
This paper proposes a new omni‐directional mobile mechanism using traveling wave based on a snail locomotion. Since the locomotion mechanism of the snail involves moving a larger area than is the case with other creatures, it is able to move not only on irregular ground such as swamps, but also on walls and ceilings. Hence, it is thought that this robot could be applied to the inspection of walls.
Details
Keywords
The purpose of this paper is to propose an imaging process method for automatically extracting assessment target regions in images of crystallization wells.
Abstract
Purpose
The purpose of this paper is to propose an imaging process method for automatically extracting assessment target regions in images of crystallization wells.
Design/methodology/approach
The proposed method detects the target by image processing based on saturation variance in images of crystallization wells.
Findings
The proposed method shows high accurate detection performance in a short time.
Practical implications
The method is applicable to automatic crystallization machine. Especially, it is expected to implement to TERA system of RIKEN.
Originality/value
The paper demonstrates target area detection from microscope images based on saturation variance in images of crystallization wells.