No abstract

This paper addresses three issues of motion planning for zero-moment point (ZMP)-based biped robots. First, three methods have been compared for smooth transition of biped locomotion from the single support phase (SSP) to the double support phase (DSP) and vice versa. All these methods depend on linear pendulum mode (LPM) to predict the trajectory of the center of gravity (COG) of the biped. It has been found that the three methods could give the same motion of the COG for the biped. The second issue is investigation of the foot trajectory with different walking patterns especially during the DSP. The characteristics of foot rotation can improve the stability performance with uniform configurations. Last, a simple algorithm has been proposed to compensate for ZMP deviations due to approximate model of the LPM. The results show that keeping the stance foot flat at beginning of the DSP is necessary for balancing the biped robot.

Cyber-Physical Systems constitute one of the core concepts in Industry 4.0 aiming at realizing production systems that combine the efforts of human workers, robots, and intelligent entities. This is particularly crucial in Human-Robot Collaboration manufacturing where a tight peer-to-peer interaction between humans and intelligent autonomous robots is necessary. The work proposes the integration of novel Artificial Intelligence technologies to enhance the flexibility and adaptability of collaborative robots. The integrated functionalities allow a collaborative robot to autonomously recognize the tasks a human worker performs, and accordingly adapt its behavior. The approach is deployed on a real HRC scenario showing the functioning of the developed cognitive capabilities and the increased flexibility of resulting collaborations.

As labor shortage is rising at an alarming rate, it is imperative to enable all people to work, particularly people with disabilities and elderly people. Robots are often used as universal tool to assist people with disabilities. However, for such human-robot workstations universal design fails. We mitigate the challenges of selecting an individualized set of input and output devices by matching devices required by the work process and individual disabilities adhering to the Convention on the Rights of Persons with Disabilities passed by the United Nations. The objective is to facilitate economically viable workstations with just the required devices, hence, lowering overall cost of corporate inclusion and during redesign of workplaces. Our work focuses on developing an efficient approach to filter input and output devices based on a person's disabilities, resulting in a tailored list of usable devices. The methodology enables an automated assessment of devices compatible with specific disabilities defined in International Classification of Functioning, Disability and Health. In a mock-up, we showcase the synthesis of input and output devices from disabilities, thereby providing a practical tool for selecting devices for individuals with disabilities.*This work was co-funded by the German Federal Ministry of Labour and Social Affairs from the "Ausgleichsfond" as part of the project "Inklusion und Integration durch Cobots auf dem ersten Arbeitsmarkt" (AGF.00.00009.22) and by RWTH Innovation GmbH in "Innovation Sprint".†Both authors contributed equally to this research.

No abstract