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Milan, IL, United States

Kerno Jr. S.,Deere and Co.
Mechanical Engineering | Year: 2010

The past few years have turned many organizations, both in the US and abroad, on their proverbial heads. Industries as diverse as banking, automobile manufacturing, and insurance were once perceived as stable and secure. Reacting to game changing developments in a company's core market or attempting to address fundamental problems within an organization is rarely an easy task. Leaders have to consider efforts to implement new practices against the forces, both internal and external to the firm, that are likely to resist and obstruct change. These countervailing forces may be pressures applied by employees, managers, customers, suppliers, lenders, insurers, activists, or any group which believes it has the potential to be impacted by a company's decisions. Doing so might have enabled entire industries to provide compensation and other benefits more in line with competitors, and could have potentially saved thousands, and perhaps even millions, of jobs. Source


Paredis C.J.J.,Georgia Institute of Technology | Bernard Y.,Airbus | Burkhart R.M.,Deere and Co. | de Koning H.-P.,European Space Agency | And 4 more authors.
20th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2010 | Year: 2010

This paper provides an overview of the formal transformation between the two complementary languages: OMG SysMLTM and Modelica. SysML is a standardized general purpose graphical modeling language for capturing complex system descriptions in terms of their structure, behavior, properties, and requirements. Modelica is a standardized general purpose systems modeling language for analyzing the continuous and discrete time dynamics of complex systems in terms of differential algebraic equations. Integrating the descriptive power of SysML models with the analytic and computational power of Modelica models provides a capability that is significantly greater than provided by SysML or Modelica individually. A standardized bi-directional transformation between the two modeling languages is being developed that will support implementations to transfer efficiently and automatically the modeling information between SysML and Modelica models without ambiguity. In addition to an overview of this bi-directional transformation approach, the paper provides a simple example to clarify the transformation principles and to illustrate the important synergies resulting from the integration between these two languages. © 2010 by Christiaan J.J. Paredis. Source


Moorehead S.J.,Deere and Co. | Wellington C.K.,Carnegie Mellon University | Paulino H.,Deere and Co. | Reid J.F.,Deere and Co.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

The R-Gator is an unmanned ground vehicle built on the John Deere 6×4 M-Gator utility vehicle chassis. The vehicle is capable of operating in urban and off-road terrain and has a large payload to carry supplies, wounded, or a marsupial robot. The R-Gator has 6 modes of operation: manual driving, teleoperation, waypoint, direction drive, playback and silent sentry. In direction drive the user specifies a direction for the robot. It will continue in that direction, avoiding obstacles, until given a new direction. Playback allows previously recorded paths, from any other mode including manual, to be played back and repeated. Silent sentry allows the engine to be turned off remotely while cameras, computers and comms remain powered by batteries. In this mode the vehicle stays quiet and stationary, collecting valuable surveillance information. The user interface consists of a wearable computer, monocle and standard video game controller. All functions of the R-Gator can be controlled by the handheld game controller, using at most 2 button presses. This easy to use user interface allows even untrained users to control the vehicle. This paper details the systems developed for the R-Gator, focusing on the novel user interface and the obstacle detection system, which supports safeguarded teleoperation as well as full autonomous operation in off-road terrain. The design for a new 4-wheel, independent suspension chassis version of the R-Gator is also presented. © 2010 SPIE. Source


Womac A.R.,University of Tennessee at Knoxville | Hart W.E.,University of Tennessee at Knoxville | Bitra V.S.P.,University of Tennessee at Knoxville | Kraus T.,Deere and Co.
Applied Engineering in Agriculture | Year: 2012

Commercial hay and forage equipment was tested for biomass harvesting of high-yield, low-moisture switchgrass for overall suitability, mass throughput rate, and effects on switchgrass drying at a southeast U.S. location. Equipment included disc mower, mower conditioner, tedder, rotary rake, round baler, and forage harvester operated in switchgrass yielding up to 12.4 Mg DM/ha. A one-cut annual switchgrass harvest during winter was investigated for equipment handling of voluminous, light (dry) material. A first of two-cut harvest during summer was investigated for infield switchgrass drying. Equipment throughput rate was presented for different losses, since machinery performance reporting is not fully standardized on the basis of productivity losses. Results showed that a disc mower equipped with a safety curtain became plugged with switchgrass from a one-cut harvest due to reduced clearance to material flow created by the curtain support. The mower conditioner operated in straight-standing, one-cut switchgrass at speeds up to 16.4 km/h and throughput rate up to 57 Mg DM/h. However, in extremely lodged switchgrass, the mower conditioner had to be operated at reduced speeds to minimize plugging. The pto-powered rotary rake handled the dry voluminous material well. The round baler performed at a maximum throughput rate of 48 Mg DM/h at 14.0 km/h. Throughput rates measured for mower conditioner and round baler were greater than previously reported, even when considering different productivity losses. The round baler equipped with a MegaWide™ Plus pickup did not limit baler performance as previously reported for other pickups. However, baler limitations were noted for switchgrass stems not aligned with the pickup, hitch entanglement with voluminous windrows, and collection of late season broken fines at critical baler locations. Mean round bale density ranged from 136 kg DM/m3 for the first of two-cut harvest in the summer to 168 kg DM/m3 for one-cut harvest in the winter. Maximum bale density was 173 kg DM/m3 for net-wrapped one-cut harvest. Mean bale density of twined bales was significantly less (p≤0.05) than bale density for net-wrapped bales for the one-cut harvest. The forage harvester operated without problem at 3.2 km/h and produced particle geometric mean dimensions of 15.3 mm for the first of two-cut harvest in the summer compared to 8.5 mm for the one-cut harvest in the winter for the same theoretical length of cut. The mower-conditioner and tedder harvest treatment promoted rapid switchgrass drying from 67% to 18% moisture content (wet basis) within 48 h after cutting. The mowed and tedded treatment reached 23% moisture content in 188 h. The Rotz drying model predicted moisture contents that fell between the mower and mowerconditioner treatments for elapsed times up to 72 h after cutting, but the model response to tedding and precipitation resulted in increased differences between predicted and actual values. Overall, current hay and forage harvest equipment have improved capacity, but high-yielding voluminous, light switchgrass exposed equipment limitations. © 2012 American Society of Agricultural and Biological Engineers. Source


Kohanbash D.,Carnegie Mellon University | Bergerman M.,Carnegie Mellon University | Lewis K.M.,Washington State University | Moorehead S.J.,Deere and Co.
American Society of Agricultural and Biological Engineers Annual International Meeting 2012, ASABE 2012 | Year: 2012

Sixty years after debuting in industrial environments, robots are making their way into our everyday life. Farmers have benefited for some time from self-guided machinery including combines and harvesters. More recently, multi-purpose autonomous vehicles have started to be deployed in orchards, groves, nurseries, and other agricultural environments to automate or augment operations such as pruning, thinning, harvesting, mowing, and spraying. Successful commercialization of such vehicles will depend heavily on them being able to operate safely and avoid accidents involving humans, animals, trees, and farm infrastructure. We propose a safety architecture to guide the design and deployment of autonomous agricultural vehicles and their introduction into production environments. The architecture spans the three elements that, combined, should ensure safe operation over a wide spectrum of applications: (1) a distributed, sensor-based, intelligent decision-making system that coordinates and guides fleets of vehicles in and around orchards and other agricultural environments; (2) multimodal interfaces for workers to interact with the vehicles using natural language, gestures, and portable devices; (3) a comprehensive regulatory framework of standards for vehicle safety that covers everything from basic robotic technology to advanced behaviors. In this paper we present the fundamental aspects of this agricultural robotic safety architecture. We illustrate its application with examples of autonomous agricultural vehicles we developed in the past that lay down the path toward full introduction of safe, intelligent machines in agricultural production environments. Source

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