People with disabilities (PwD) have the right to equal participation in the labor market under the 2008 Convention on the Rights of Persons with Disabilities [1], yet OECD data indicates that PwD remain excluded, with a 15% unemployment rate in 2019 across 32 OECD countries, and an 8.6% higher unemployment rate compared to people without disabilities [2]. With the growth of the elderly population and, consequently PwD, employers will face labor shortages [3]. The European Commission advocates for technology, like human-robot collaboration, to create ergonomic workplaces adapted to individual needs, aiming to enhance PwD inclusion and alleviate labor shortages [4].

Safety is a central challenge in human-robot collaboration. Particularly in higher collaboration levels, separating safety devices, such as fences, are no longer needed and must be replaced by intelligent sensor-based systems. Of particular interest is the adaptive speed control of the robot. This work presents a methodology to adaptively control the end-effector velocity of the robot based on the distances to dynamic environmental objects. The method combines distance measurement and environmental subtraction with conservative velocity estimation using robot-specific stopping distances and is available in real-time. Data acquisition is performed using a co-moving 3D camera sensor attached to the robot structure.

Human-robot collaboration offers the advantage of combining human characteristics and robotic capabilities, balancing individual weaknesses. In the inclusive project Next Generation, we are exploring the possibility of using collaborative robots as assistive devices for people with severe and multiple disabilities. An important step in implementing an inclusive workstation with a collaborative robot is determining the level of assistance required. Therefore, we developed a novel methodology and a capability-based software tool to determine the individual level of challenge. In this paper, we present the developed tool and its validation. We validate the methodology and tool using an industrial sample application from first labor market incorporating participants with varying mental and physical disabilities.

The increasing energy consumption within the industrial sector causes great concerns among numerous countries. Accordingly, an extensive reorientation towards an energy-efficient facility and processes design is essential for innovative production systems. In terms of automated object manipulation, energy efficiency significantly is affected by the physical design as well as by the dynamic characteristics of the manipulator. Since the influence on physical design parameters often is limited, a great impact on energy-efficiency of innovative manufacturing systems may result from an intelligent task management and suitable motion strategies. This contribution identifies energy-efficiency potentials for industrial manipulators in terms of motion design and redundant actuator configurations. In this context, an efficient trajectory planning algorithm is proposed, estimating the energy demand of object manipulation tasks in consideration of dynamic motion parameters as well as redundant actuator configurations. For this purpose, the geometric path as well as the motion law of given trajectories are optimized by a spatial displacement of predefined nodes and by an adjustment of corresponding time intervals. In order to verify its generality, the presented method is applied to the spatial n-PRPaR manipulator exhibiting actuation redundancy. According results show a significant energy reduction, establishing high potentials for an increased efficiency of industrial robots.

Precision is an important feature in modern robotics and manipulation technology. Elevation of the robot's end-effector precision depends on different features as stiffness, tolerance etc. which should be considered during the synthesis and design phase of the manipulator. The focus of this study is on the structural stiffness of parallel kinematic manipulators (PKM) exhibiting actuation redundancy. It is determined how the stiffness depends on physical and geometrical characteristics of the manipulator and how it is possible to take advantage of redundancy to enhance the stiffness of the manipulator. It is shown that redundantly actuated PKM (RA-PKM) with components made of softer and accordingly lighter materials demonstrate comparable stiffness to the non-redundant manipulators which consequently decrease the required energy for moving the dead-load in operation. Based on the model built in this study, optimizations are conducted and manipulators with optimal morphologies for different tasks are introduced. As a case study, RA-PKM of type n-R RPaRs are considered.