Interconnection of Modules of Reconfigurable Modular Robots: A Review
DOI:
https://doi.org/10.51983/ajeat-2012.1.2.2494Keywords:
Self-reconfigurable Modular Robots, Simulation, Image Recognition, Module Docking, MatLabAbstract
Robots normally perform pre-specified tasks in a predictable environment, like that on shop floor. Normally, assembly-line like operations are performed by robots due to geometrical and programming constraints. Rapidly changing requirments at customer level has greatly influenced the manufacturing technology, due to the risk of obsolescence. Multiple small robots called modules, interconnect with each other its own, to make a great structure are called self reconfigurable modular robots. For few modules, a large number of configurations are possible. As per the level of difficulty of the task, it can take any shape, to complete the work. Each module of the modular robot has its built-in intelligence with separate memory, connection assemblies, detectors and actuators to operate it. Such robots are highly useful in remote operations, especially in hostile environments. For physical docking of the connection plates of the modules, the connection plates should be properly aligned towards each other. This review paper enlightens the capabilities of the modular reconfigurable robots and the techniques explored by some researchers in this field, for proper alignment of the connection plates, for physical docking of modules. Position sensors like hall-effect sensors; and proximity sensors like infrared (IR) detectors and emitters have been used for docking of connection plates of the modules. Controlling and coordinating modules to work together effectively and not collide or otherwise interfere with each other is a bottleneck in this concept. Some work using IR intensity to guide the alignment of the modular robots have already been undertaken. Possibility for the use of MatLab by Mathworks is explored to simulate the alignment for interconnection of Modules of Reconfigurable Modular Robot using data captured by the CCD camera through image recognition.
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