Inertial human motion capture (IHMC) has become a robust tool to estimate human kinematics in the wild such as industrial facilities. In contrast to optical motion capture, where occlusions might take place, the kinematics of a worker can be continuously provided. This is for instance a prerequisite for an ergonomic assessments of the workers. State-of-the-art IHMC solutions require inertial sensors to be tightly attached to body segments. This requires an additional setup time and lowers the practicability and ease of use when it comes to an industrial application. In contrast, sensors integrated into loose clothing such as a working jacket, may yield corrupted kinematics estimates due to the additional motion of loose clothing. In this work we present a study of orientations deviations obtained from kinematics estimates using tightly attached inertial sensors and into a working jacket integrated ones. We performed a quantitative analysis using data from the two hardware setups worn by 19 subjects performing different industry related tasks and measures of their body shapes. Using this data we approximated probability distributions of the deviation angles for each person and body segment. Applying different statistical measures we could gain insights to questions like, how severe orientation deviations are, if there is an influence of body shapes on the distribution and how probability distributions of the deviation angles can indicate physical motion limitations of a sensor attached to a segment.

Inertial motion capture has become an attractive alternative to optical motion capture for human joint angle estimation outside the laboratory. Usually inertial sensors are assumed to be tightly fixed to the body segments, which can be cumbersome regarding setup-time and ease-of-use. However, integrating the sensors directly into loose clothing, usually, results in additional clothing motion relative to the motion of the underlying bones that should be captured. In this work we propose the Difference Mapping distributions approach that corrects the segment orientations of a given inertial motion capture system that assumes tightly coupled sensors. The approach allows to reduce the joint angle errors due to clothing artefacts by at least 77.2% for people with similar morphology performing a similar task as seen in the training data, including an ergonomic assessments scenario at work places with ten participants. Moreover, we show that the uncertainty of the distribution can be used to measure the reliability of the predicted map if e.g. the motion is further away from the training data to allow for an artefact aware inertial motion tracking approach. The experimental data for this study is available online under [1].

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.

Spatial object manipulation is typically accomplished by parallel kinematic manipulators (PKM), whose number of actuators is equal to the required number of degrees of freedom. In order to improve the performance and reliability of PKM, their basic configuration can be extended by redundant actuators. This paper is devoted to the special case of PKM with both linear and rotational actuation, which can be operated simultaneously. Corresponding manipulators face the problem of coexisting translational and rotational joint space parameters inducing inhomogeneous Jacobian matrices. In this context, power manipulability ellipsoids provide a suitable performance evaluation for PKM featuring different types of redundantly applicable actuators. Accordingly, this research intends to analyze the kinetostatic performance of redundantly actuated PKM and to demonstrate their efficiency in contrast to non-redundant drive configurations. The analyses exemplarily are focused on the translational 3-RPC manipulator, since it can be equipped with both revolute and/or prismatic joint actuation.

Due to excellent dynamic properties and high precision, parallel manipulators are particularly suited for high-speed and high-accuracy object handling. For this reason, the design process of parallel manipulators is usually supposed to optimize the manipulators' dexterity or structural stiffness. Accordingly, this research intends to analyze the effects of changing actuator and frame-configurations regarding the handling performance of a class of translational 3-RPC-manipulators. Since the RPC-structure can be arranged with translational and/or rotational actuators, several different drive configurations are possible. Additionally, four different frame configurations can be identified, expanding the number of possible manipulators. In order to find an optimized actuator and frame configuration for a given task, this research approach systematically reduces the number of possible configurations by means of validity detection and kinetostatic performance analysis. Hence, it is shown that good performance can be achieved for all frame configurations by selecting a suitable actuator combination.