Using Full Pose Measurement for Serial Robot Calibration.

To ensure smooth robot operations, parameters of its kinematic model and a registration transformation between robot base and world coordinate frame must be determined. Both tasks require data acquired by external sensors that can measure either 3D locations or full 6D poses. We show that use of full pose measurements leads to much smaller robot orientation errors when compared with the outcome of calibration and registration procedures based on 3D data only.

Comparative Study of Two Pose Measuring Systems Used to Reduce Robot Localization Error.

The performance of marker-based, six degrees of freedom (6DOF) pose measuring systems is investigated. For instruments in this class, the pose is derived from locations of a few three-dimensional (3D) points. For such configurations to be used, the rigid-body condition-which requires that the distance between any two points must be fixed, regardless of orientation and position of the configuration-must be satisfied.

Multi-Robot Assembly Strategies and Metrics.

We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles.

Strategies for Improving and Evaluating Robot Registration Performance.

Unlabelled: The ability to calculate rigid-body transformations between arbitrary coordinate systems (i.e., registration) is an invaluable tool in robotics.

Implementing Speed and Separation Monitoring in Collaborative Robot Workcells.

We provide an overview and guidance for the Speed and Separation Monitoring methodology as presented in the International Organization of Standardization's technical specification 15066 on collaborative robot safety. Such functionality is provided by external, intelligent observer systems integrated into a robotic workcell. The SSM minimum protective distance function equation is discussed in detail, with consideration for the input values, implementation specifications, and performance expectations.

Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems.

The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM leverages and integrates lower-level PHM information such as from a machine or component with hierarchical relationships across the component, machine, work cell, and assembly line levels in a manufacturing system.

Adaptive Multi-scale PHM for Robotic Assembly Processes.

Adaptive multiscale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. As a rule, PHM information is not used in high-level decision-making in manufacturing systems. AM-PHM leverages and integrates component-level PHM information with hierarchical relationships across the component, machine, work cell, and production line levels in a manufacturing system.