In the last decades, increasing energy prices and growing environmental awareness have driven engineers and scientists to find new solutions for reducing energy consumption in manufacturing. Although many processes of a high energy consumption (e.g., chemical, heating, etc.) are considered to have reached high levels of efficiency, this is not the case for many other industrial manufacturing activities. Indeed, this is the case for robotic and automatic systems, for which, in the past, the minimization of energy demand was not considered a design objective. The proper design and operation of industrial robots and automation systems represent a great opportunity for reducing energy consumption in the industry, for example, by the substitution with more efficient systems and the energy optimization of operation. This review paper classifies and analyses several methodologies and technologies that have been developed with the aim of providing a reference of existing methods, techniques and technologies for enhancing the energy performance of industrial robotic and mechatronic systems. Hardware and software methods, including several subcategories, are considered and compared, and emerging ideas and possible future perspectives are discussed.

Design optimization of flexible multibody dynamics is critical to reducing weight and therefore increasing efficiency and lowering costs of mechanical systems. Simulation of flexible multibody systems, though, typically requires high computational effort which limits the usage of design optimization, especially when gradient-free methods are used and thousands of system evaluations are required. Efficient design optimization of flexible multibody dynamics is enabled by gradient-based optimization methods in concert with analytical sensitivity analysis. The present study summarizes different formulations of the equations of motion of flexible multibody dynamics. Design optimization techniques are introduced, and applications to flexible multibody dynamics are categorized. Efficient sensitivity analysis is the centerpiece of gradient-based design optimization, and sensitivity methods are introduced. The increased implementation effort of analytical sensitivity analysis is rewarded with high computational efficiency. An exemplary solution strategy for system and sensitivity evaluations is shown with the analytical direct differentiation method. Extensive literature sources are shown related to recent research activities.

Collaborative robots are among the key enabling technologies of the fourth industrial revolution and have the potential to change the way people and machines physically interact. Such collaborative robotics applications can be successful in small- and medium-sized enterprises (SMEs) only if they are properly implemented, taking into account safety and ergonomics of the shared workplace. This chapter first reviews safety standards, methods for risk assessment, and the concept of ergonomics of workplaces. The chapter discusses why collaborative robotics can be seen as important potential for SMEs and what the challenges are that SMEs are facing when implementing collaborative workspaces in the company. In conclusion, the chapter gives recommendations for future topics of research to overcome the barrier to introducing smart automation in SMEs.

Energy saving in robotic and mechatronic systems is becoming an evermore important topic in both industry and academia. One strategy to reduce the energy consumption, especially for cyclic tasks, is exploiting natural motion. We define natural motion as the system response caused by the conversion of potential elastic energy into kinetic energy. This motion can be both a forced response assisted by a motor or a free response. The application of the natural motion concepts allows for energy saving in tasks characterized by repetitive or cyclic motion. This review paper proposes a classification of several approaches to natural motion, starting from the compliant elements and the actuators needed for its implementation. Then several approaches to natural motion are discussed based on the trajectory followed by the system, providing useful information to the researchers dealing with natural motion.

Collaborative robotics is one of the main drivers of the fourth industrial revolution where robots and humans cooperate in a shared workspace. Such kind of robots are distinguished from the traditional robots by several features that, if tuned correctly, ensure safe physical interaction. How- ever, robots also represent a potential source of psychological stress. Indeed, it has been proven that working and sharing the workspace with robots can psychologically stress the operator. This drawback — in addition to the reduced speed operation imposed by safety standards — represent a constraint difficult to bear in small and medium-sized enterprises (SME), due an inherent lack of expertise in robotics. In this paper, we propose a novel trajectory planner for collaborative robots able to ensure both psychological and physical safety. We rely on available literature and the calculus of variations to identify a family of psychologically acceptable minimum-jerk trajectories. From such family we compute the fastest trajectory that limits the physical danger represented by the robot. A numerical implementation of the method is discussed and experimental results prove the effectiveness of the idea