Experiments on Design of Obstacle Avoiding Robots Based on Sensors, Bluetooth, and IoT

Experiments on Design of Obstacle Avoiding Robots Based on Sensors, Bluetooth, and IoT

Shirshak Kumar (CSIR-CSIO, Chandigarh, India), Suraj (CSIR-CSIO, Chandigarh, India), Sahil Sandhu (CSIR-CSIO, Chandigarh, India), Narinder Singh Jassal (CSIR-CSIO, Chandigarh, India), Jitendra Virmani (CSIR-CSIO, Chandigarh, India) and Kriti (Thapar Institute of Engineering and Technology, India)
DOI: 10.4018/978-1-5225-9574-8.ch006

Abstract

The mobile robotics industry is related to creating mobile robots that can move around in physical environments. Different types of mobile robot designs for obstacle avoidance have been experimented in the past based on different sensors, trajectory algorithms, etc. The chapter presents implementation details of different obstacle avoiding robots (OARs) using sensors, Bluetooth module, and IoT modules. The sensor-based obstacle-avoiding robots are designed using ultrasonic sensors and Arduino microcontrollers. Bluetooth-based obstacle-avoiding robots have been designed using Arduino mega and Bluetooth module and an Android application. IoT-based obstacle-avoiding robots can be designed in three different ways, using ethernet shield, node MCU, or Raspberry Pi. The IoT-based obstacle-avoiding robot using Raspberry Pi is the most popular mobile robot model that uses maximum on-chip modules in comparison to other designs, and also, the design can be extended by using cameras to use images for sensing the objects in order to avoid collisions.
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Literature Survey

Many attempts have been made in the past for the design of autonomous mobile robots. All these differ basically in the choice of sensors used, mapping of the path to be followed, the operations used to set the operational parameters and the hardware platform utilized.

The designs of the obstacle avoiding robots (OARs) discussed in the chapter are shown in Figure 1.

Figure 1.

The designs of the obstacle avoiding robots (OARs) discussed in the chapter

978-1-5225-9574-8.ch006.f01

Tabassum et al. (2017) presented the design of an obstacle avoiding robot using Arduino microcontroller and three ultrasonic sensors for obstacle detection.

Chen et al. (2009) designed two models of a wheeled mobile robot for obstacle avoidance. The two models were named: Model 1: short-distance obstacle avoidance model and Model 2: target-driven obstacle avoidance model. The first model makes use of the ultrasonic sensors for avoiding the obstacles while the target-driven model makes use of fuzzy logic along with the sensor signals for speed control.

Yang et al. (2010) presented an intelligent mobile robot design for avoiding obstacles using multiple ultrasonic sensors and fuzzy control rules. All the programming has been performed in the VC environment using C and Colbert language.

Xiong et al. (2011) analyzed the movement of the designed robot under complex unknown environments. The robot’s obstacle avoiding algorithm is based on MIMO fuzzy rules on the basis of the shape analysis of the obstacle.

Boujelben et al. (2013) proposed an approach that is based on a hierarchical Fuzzy controller for designing an obstacle avoiding robot which can be placed in an unknown environment containing mobile obstacles.

Yamada et al. (2013) proposed a robot design that follows a designated path by avoiding mobile obstacles. In order to scan the region for obstacles, two laser sensors (one at the front and one at back) have been used.

Bhagat et al. (2016) designed an obstacle avoiding robot using ultrasonic sensors and ATMEGA-8 microcontroller.

Wu et al. (2014) used 6 ultrasonic sensors and ATMEGA 162 microcontroller to design an obstacle avoiding system on the wheeled robot that continuously scans its surroundings to avoid the obstacles while moving towards the desired target. A PD controller was also integrated into the design for the wall-following method so that the robot could avoid large obstacles.

Jathavara et al. (2017) designed an obstacle avoiding robot based on ultrasonic sensors and a biologically inspired learning method to compute the location and speed of the obstacle such that robot could compute a time window within which it completes its movement to avoid the obstacle.

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