At the beginning of a project or research that involves the issue of autonomous navigation of mobile robots, a decision must be made about working with traditional control algorithms or algorithms based on artificial intelligence. This decision is not usually easy, as the computational capacity of the robot, the availability of information through its sensory systems and the characteristics of the environment must be taken into consideration. For this reason, this work focuses on a review of different autonomous-navigation algorithms applied to mobile robots, from which the most suitable ones have been identified for the cases in which the robot must navigate in dynamic environments. Based on the identified algorithms, a comparison of these traditional and DRL-based algorithms was made, using a robotic platform to evaluate their performance, identify their advantages and disadvantages and provide a recommendation for their use, according to the development requirements of the robot. The algorithms selected were DWA, TEB, CADRL and SAC, and the results show that—according to the application and the robot’s characteristics—it is recommended to use each of them, based on different conditions.

In recent years, social assistive robots have gained significant acceptance in healthcare settings, particularly for tasks such as patient care and monitoring. This paper offers a comprehensive overview of the expressive humanoid robot, Qhali, with a focus on its industrial design, essential components, and validation in a controlled environment. The industrial design phase encompasses research, ideation, design, manufacturing, and implementation. Subsequently, the mechatronic system is detailed, covering sensing, actuation, control, energy, and software interface. Qhali’s capabilities include autonomous execution of routines for mental health promotion and psychological testing. The software platform enables therapist-directed interventions, allowing the robot to convey emotional gestures through joint and head movements and simulate various facial expressions for more engaging interactions. Finally, with the robot fully operational, an initial behavioral experiment was conducted to validate Qhali’s capability to deliver telepsychological interventions. The findings from this preliminary study indicate that participants reported enhancements in their emotional well-being, along with positive outcomes in their perception of the psychological intervention conducted with the humanoid robot.

In social robotics, especially with regard to direct interactions between robots and humans, the robotic movements of the body, arms and head must make an adequate displacement to guarantee an adequate interaction, both from a functional and social point of view. To achieve this, the use of closed-loop control techniques that consider the complex nonlinear dynamics and disturbances inherent in these systems is required. In this paper, an implementation of a nonlinear controller for the tracking of trajectories and a profile of speeds that execute the movements of the arms and head of a humanoid robot based on the mathematical model is proposed. First, the design and implementation of the arms and head are initially presented, then the mathematical model via kinematic and dynamic analysis was performed. With the above, the design of nonlinear controllers such as nonlinear proportional derivative control with gravity compensation, Backstepping control, Sliding Mode control and the application of each of them to the robotic system are presented. A comparative analysis based on a frequency analysis, the efficiency in polynomial trajectories and the implementation requirements allowed selecting the non-linear Backstepping control technique to be implemented. Then, for the implementation, a centralized control architecture is considered, which uses a central microcontroller in the external loop and an internal microcontroller (as internal loop) for each of the actuators. With the above, the selected controller was validated through experiments performed in real time on the implemented humanoid robot, demonstrating proper path tracking of established trajectories for performing body language movements.