Leandro Barajas

Dynetics · Unmanned Systems and Aerodynamics

A method for training a robot to execute a robotic task in a work environment includes moving the robot across its configuration space through multiple states of the task and recording motor schema describing a sequence of behavior of the robot. Sensory data describing performance and state values of the robot is recorded while moving the robot. Th...

Methods and apparatus for procedural memory learning to control a robot by demonstrating a task action to the robot and having the robot learn the action according to a similarity matrix of correlated values, attributes, and parameters obtained from the robot as the robot performs the demonstrated action. Learning is done by an artificial neural ne...

A method and system for characterizing, detecting, and predicting or forecasting multiple target events from a past history of these events includes compressing temporal data streams into self-organizing map (SOM) clusters, and determining trajectories of the temporal streams via the clusters to predict the multiple target events. The system includ...

A system associated with handling an object with a gripper includes a sensor that is configured to measure spatially distributed data that represents the position of the object that is handled by the gripper. The system further includes a computing unit that is configured to determine the behavior of the object.

The wide spread availability of real-time plant floor systems PFS information has made the modern automotive assembly line a data-rich environment. Information from these data sources offers an unprecedented opportunity to model and simulate the performance of an assembly line as a dynamic system, as opposed to a conventional static manner. The dyn...

A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and heal...

Industries are being swept up by the tide of market innovations originated from pervasive application of Robotics and Automation (RA). Given the critical role of RA in industry, it has become relevant for RA to have human-like decision making capabilities. Such enablers intrinsically require the use of flexible and robust 3D perception and control...

Advances in design and fabrication technologies are enabling the production and commercialization of sensor-rich robotic hands with skin-like sensor arrays. Robotic skin is poised to become a crucial interface between the robot embodied intelligence and the external world. The need to fuse and make sense out of data extracted from skin-like sensors...

This paper presents a local recurrence modeling approach for state and performance predictions in complex nonlinear and nonstationary systems. Nonstationarity is treated as the switching force between different stationary systems, which is shown as a series of finite time detours of system dynamics from the vicinity of a nonlinear attractor. Recurr...

Since the 1980s, the manufacturing environment has seen the introduction of numerous sensor/actuator bus and network protocols for automation systems, which led to increased manufacturing productivity, improved interchangeability of devices from different vendors, facilitated flexibility and reconfigurability for various applications and improved r...

Kitting processes are fundamental enablers in flexible manufacturing environments derived from minomi principles. A typical kitting application will sort loose and unpacked parts without dunnage into a tray or “kit” and then place them near the point of assembly for easy reach by assembly workers. In order to prepare, sort and sequence the kits, it...

In the automotive industry an integrated set of manufacturing engineering activities lie on the critical path of the Vehicle Development Process (VDP). After the product integration design is finalized, the Production Tool Design and Build (PTDB) processes becomes the VDP critical path. It is in the PTDB where virtual launch and validation activiti...

This paper describes a genetic algorithm based approach to detect and predict high-impact events. While, these events occur infrequently, they are quite costly, meaning that they have a high-impact on the system key performance indicators. This approach is based on mining for these events and subsequences that are predictive of these high-impact ev...

Modern manufacturing enterprises have invested in a variety of sensors and IT infrastructure to increase plant floor information visibility. This offers an unprecedented opportunity to track performances of manufacturing systems from a dynamic, as opposed to static, sense. Conventional static models are inadequate to model manufacturing system perf...

This paper presents a neural network model for the stencil printing process (SPP) in surface-mount technology (SMT) manufacturing of printed circuit boards (PCBs). A practical model description that decomposes the overall steady-state process in independently modeled subspaces is provided. The neural network model can be updated in real-time procur...

Traditional technologies emphasize either experience or model-based approaches to the Diagnostics, Prognostics and Health Management (DPHM) problem. However, most of these methodologies often apply only to the narrow type of machines that they were developed for, and only support strategic level assessments as opposed to real-time tactical decision...

In this paper, we develop a hybrid control algorithm that produces control values for processes where only a limited number of function evaluations are available for the control law generation. This situation arises, for example, in stencil printing processes in printed circuit board manufacturing, where the cost associated with multiple function e...

In this paper we show how hybrid control and modeling tech-niques can be put to work for solving a problem of industrial relevance in Surface Mount Technology (SMT) manufacturing. In particular, by closing the loop over the stencil printing process, we obtain a robust system that can recover from faulty initial settings, adapt to environ-mental cha...

Ph.D. Magnus Egerstedt

In this paper a control algorithm, that generates adequate machine settings for the Stencil Printing Process (SPP) in Surface Mount Technology manufacturing, is presented. The SPP is characterized by high process-noise levels, and by requiring constant solder-paste volume deposition at all times. Due to the prohibitive cost associated with extensiv...

The number of defects in stencil printing can be reduced by using feedback control, based on AOI measurements of the deposited solder paste bricks.

This work presents a parallel hybrid control system that uses as main tools Fuzzy Logic and Artificial Neural Networks (ANN), showing the practical applications that these technologies have in the industry. Neural-Fuzzy Embedded Control System (SCINEF) was applied to the control of a 1MW power generator to optimize its set point, diminishing in tha...