The field of assistive robotics is experiencing rapid growth due to recent advancements in computing, control systems, and instrumentation. Physiotherapeutic methods, such as gait rehabilitation and learning, are frequently deployed to teach and aid individuals with disabilities, particularly children with cerebral palsy (CP), as enhancing mobility is crucial for their overall health and future independence. These methods can be enhanced through assistive technologies, which can streamline treatment, reduce the physical burden on physiotherapists, boost the efficiency of therapeutic techniques, and improve the precision and consistency of therapeutic movements. This work introduces the modeling, control, and prototyping of an omnidirectional mobile platform designed for assistive robotics applications, with the goal of expanding movement possibilities during rehabilitation. The paper addresses issues like the impact of holonomic approximations on dynamic modeling, proposes a control architecture, and presents a cost-effective generalized omnidirectional robotic platform integrated with ROS as a physical scale prototype.

In today's rapidly evolving industry, new challenges constantly arise that must be addressed quickly to keep up with the growing demand. Industry 5.0 aims to eliminate ob-stacles in production lines and integrate intelligent systems into manufacturing without excluding human operators from their daily tasks. In this context, developing software for controlling and managing data-driven evidence in the production cells becomes essential when considering performance, reliability, and practical aspects, as well as the financial returns it can bring to organizations. This work presents a brief overview of such an approach, proposing the development of a software architecture that manages industrial quality inspection in automotive parts using an Internet of Things publisher/subscriber model for controlling and synchronizing sub-processes. The results obtained demonstrate the benefits of implementing a control and evidence management system, offering production operators online monitoring of failures in manufactured parts and effective visualization of evidence of failures. This helps in decision-making and integrates the operator (user) with the system, which aligns with Industry 5.0 principles. This contribution is supported by creating a database of quality inspection evidence that can be used to train machine learning models to detect failures more accurately in the future.

An area of robotics, assistive robotics, has been growing rapidly with recent advances in computing, control systems and instrumentation. Physio therapeutic procedures like gait rehabilitation and learning are often used for teaching and recovery of people with disabilities, especially children with cerebral palsy (CP), as the reinforcement of mobility is fundamental for the health and subsequent independence of the patient. These processes can benefit from assistive technologies to expedite the treatment, reducing physical strain of physiotherapists, increasing the efficiency of techniques and promoting better precision and repeatability for therapeutic movements. This paper presents the modeling and control of an omnidirectional mobile platform for applications in assistive robotics, aiming to expand this paradigm to incorporate greater possibilities of movement during the rehabilitation process. For this to be realized, the paper discusses questions such as the effects of holonomic approximations on dynamic modeling, proposes a control architecture, and introduces a physical prototype in the form of a low-cost generalized omnidirectional robotic platform integrated in ROS.

This paper describes a digital-twin-based approach to dimensional control designed to assist quality inspection of automotive air-conditioning rotors in the vehicle manufacturing industry. It focuses on dimensional quality control within the field of dimensional metrology, aiming to accurately measure the dimensions of parts, subassemblies, and complete equipment systems. The proposed approach has created a prototype, collecting measurement data from a test sample to generate validation results for error profiling. The main goal is to develop a method for improving the precision of sensors used for this type of quality inspection.

Rehabilitation of upper limb movements in patients with hemiparesis has been a longstanding struggle for physical therapy professionals. Tools such as robotically assisted therapies have shown great potential to assist in the rehabilitation process of patients. Regarding traditional rehabilitation interventions, robotic systems can provide more effective and intensive physical therapy as new interventions are now being used to assist in the rehabilitation of patients with certain movement restrictions especially after stroke. Currently, this research work aims to present a study on the trajectory planning of a robotic arm, which will be suggested to the patient in order to perform the movement for rehabilitation. Furthermore, it is intended that the trajectory can be generated in real time to better meet the patient’s movement requirements and restrictions. In view of the need for real-time trajectory generation, it is necessary that a simple model of the manipulator work area is used as a boundary and boundary condition for the task space. In parallel, there is the development of a prototype of the REHABOT robot, a mechanical project developed with components from the Cyton Gamma 1500 and Reachy robots.