Autonomous Food Waste Segregation Using Machine Vision and Delta Robot

Balakrishnan, Suren (2023) Autonomous Food Waste Segregation Using Machine Vision and Delta Robot. Final Year Project (Diploma), Tunku Abdul Rahman University of Management and Technology.

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Abstract

The conventional waste management method of collecting waste. This is because the waste collected is not reused. In this study, a food waste segregation system is proposed due to inefficiency human workers. However, the use of human labor to separate the waste is highly ineffective and introduces health risk to them. An autonomous system would be the optimum solution to handle this issue, as it completely removes human intervention. A Delta robot paired with Machine Vision has been proposed to solve this issue. A Delta robot has been proposed due to its high speed and accuracy. Machine vision has been chosen as it is the only sensor capable of detecting such waste used to this degree of accuracy. The machine Vision helps to identify the type of waste, similar to a human eyes and brains. The Delta robot would pick up the waste and place it into different sortation containers similar to human arms. This method is highly effective as it can be run for almost indefinitely at a very high speed and rate. Such a system can also be very easily implemented to existing facilities. The prototype assessed in this study achieved a success rate of 96%.