Seamless human–robot collaboration requires the equipping of robots with cognitive capabilities that enable their awareness of the environment, as well as the actions that take place inside the assembly cell. This paper proposes an AI-based system comprised of three modules that can capture the operator and environment status and process status, identify the tasks that are being executed by the operator using vision-based machine learning, and provide customized operator support from the robot side for shared tasks, automatically adapting to the operator’s needs and preferences. Moreover, the proposed system is able to assess the ergonomics in human–robot shared tasks and adapt the robot pose to improve ergonomics using a heuristics-based search algorithm. An industrial case study derived from the elevator manufacturing sector using a high payload collaborative robot is presented to demonstrate that collaboration efficiency can be enhanced through the use of the discussed system.

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Combined blockade of the renin-angiotensin-aldosterone system (RAAS) is an attractive therapeutic strategy for the treatment of cardiovascular diseases. Vasopeptidase inhibitors are a group of compounds capable of inhibiting more than one enzyme, which leads to potentiation of natriuretic peptide actions and suppression of the RAAS. In this study, molecular modeling has been used to elucidate key structural features that govern the binding and/or selectivity of a single compound toward the zinc catalytic sites of the N- and C-domains of the angiotensin-converting enzyme (ACE) and the neutral endopeptidase (NEP). Eleven dual inhibitors were categorized in three classes, according to their zinc binding groups. Analysis of their docked conformers revealed the molecular environment of the catalytic sites and the specific interactions between the inhibitors and amino acid residues that are important for selectivity and cooperativity. In addition, inhibitors were predicted to bind to the C-domain of the ACE with greater affinity than the N-domain, with an average difference in the free energy of binding approximately 2-3 kcal mol(-1). Residues that were identified to actively participate in the binding and stabilizing of the enzyme-inhibitor complexes were analyzed in a consensus way for both the ACE and the NEP. These atomic-level insights into enzyme-ligand binding can be used to drive new structure-based drug design processes in the quest for more selective and effective vasopeptidase inhibitors.