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This article describes the design and testing of a walking robot. In the first stage, the mechanical behaviour of human’s lower limbs during the walk was observed and described to acquire data for the development of a simplified algorithm to control the legs of a walking robot. The second phase was the designing stage of the bipedal walking. Each robotic leg was equipped with six servo-drives. A gyroscope module with an accelerometer was used to measure the current position of the robot’s structure in space. The controller of a walking robot was developed and programmed based on Arduino Mega. The control algorithm stabilises the robot in an upright position. Potentiometers placed in the axes enabled measurements of angular positions of individual servos during the movement and were used to control walking. The programming of the movement is done through a smartphone which communicates with the robot's main controller using Bluetooth. Finally, the article describes the testing of the developed bipedal walking robot, documenting satisfactory results in walking.

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Control systems that ensure robot operation during failures are necessary, particularly when manipulators are operating in hazardous or hard-to-reach environments. In such applications, fault-tolerant robot controllers should detect failures and, using fault-tolerant control methods, be able to continue operation without human intervention. Fault-tolerant control (FTC) is becoming increasingly important in all industries, including production lines in which modern robotic manipulators are used. The use of fault-tolerant systems in robotics can prevent the production line from being immobilized due to minor faults. In this paper, an overview of the current state-of-the-art methods of fault-tolerant control in robotic manipulators is provided. This review covers publications from 2003 to 2022. The article pays special attention to the use of artificial intelligence (AI), i.e., fuzzy logic and artificial neural networks, as well as sliding mode and other control methods, in the FTC of robotic manipulators. The cited and described publications were mostly found using Google Scholar.