On Modular Design of Field Robotic Systems

Robots are needed to perform important field tasks such as hazardous material clean-up, nuclear site inspection, and space exploration. Unfortunately their use is not widespread due to their long development times and high costs. To make them practical, a modular design approach is proposed. Prefabricated modules are rapidly assembled to give a low-cost system for a specific task. This paper described the modular design problem for field robots and the application of a hierarchical selection process to solve this problem. Theoretical analysis and an example case study are presented. The theoretical analysis of the modular design problem revealed the large size of the search space. It showed the advantages of approaching the design on various levels. The hierarchical selection process applies physical rules to reduce the search space to a computationally feasible size and a genetic algorithm performs the final search in a greatly reduced space. This process is based on the observation that simple physically based rules can eliminate large sections of the design space to greatly simplify the search. The design process is applied to a duct inspection task. Five candidate robots were developed. Two of these robots are evaluated using detailed physical simulation. It is shown that the more obvious solution is not able to complete the task, while the non-obvious asymmetric design develop by the process is successful.

Yield potential and resource-use efficiency of maize systems in the western U.S. Corn Belt

Maize demand for food, livestock feed, and biofuel is expected to increase substantially. The Western U.S. Corn Belt accounts for 23% of U.S. maize production, and irrigated maize accounts for 43 and 58% of maize land area and total production, respectively, in this region. The most sensitive parameters (yield potential [YP], water-limited yield potential [YP-W], yield gap between actual yield and YP, and resource-use efficiency) governing performance of maize systems in the region are lacking. A simulation model was used to quantify YP under irrigated and rainfed conditions based on weather data, soil properties, and crop management at 18 locations. In a separate study, 5-year soil water data measured in central Nebraska were used to analyze soil water recharge during the non-growing season because soil water content at sowing is a critical component of water supply available for summer crops. On-farm data, including yield, irrigation, and nitrogen (N) rate for 777 field-years, was used to quantify size of yield gaps and evaluate resource-use efficiency. Simulated average YP and YP-W were 14.4 and 8.3 Mg ha-1, respectively. Geospatial variation of YP was associated with solar radiation and temperature during post-anthesis phase while variation in water-limited yield was linked to the longitudinal variation in seasonal rainfall and evaporative demand. Analysis of soil water recharge indicates that 80% of variation in soil water content at sowing can be explained by precipitation during non-growing season and residual soil water at end of previous growing season. A linear relationship between YP-W and water supply (slope: 19.3 kg ha-1 mm-1; x-intercept: 100 mm) can be used as a benchmark to diagnose and improve farmer’s water productivity (WP; kg grain per unit of water supply). Evaluation of data from farmer’s fields provides proof-of-concept and helps identify management constraints to high levels of productivity and resource-use efficiency. On average, actual yields of irrigated maize systems were 11% below YP. WP and N-fertilizer use efficiency (NUE) were high despite application of large amounts of irrigation water and N fertilizer (14 kg grain mm-1 water supply and 71 kg grain kg-1 N fertilizer). While there is limited scope for substantial increases in actual average yields, WP and NUE can be further increased by: (1) switching surface to pivot systems, (2) using conservation instead of conventional tillage systems in soybean-maize rotations, (3) implementation of irrigation schedules based on crop water requirements, and (4) better N fertilizer management.

Measurement, Simulation, and Analysis of the Mechanical Response of Railroad Track

Increased railroad traffic volumes, speeds, and axle loads have created a need to better measure track quality. Previous research has indicated that the vertical track deflection provides a meaningful indicator of track integrity. The measured deflection can be related to the bending stresses in the rail as well as characterize the mechanical response of the track. This investigation summarizes the simulation, analysis and development of a measurement system at the University of Nebraska (UNL) to measure vertical track deflection in real-time from a car moving at revenue speeds. The UNL system operates continuously over long distances and in revenue service. Using a camera and two line lasers, the system establishes three points of the rail shape beneath the loaded wheels and over a distance of 10 ft. The resulting rail shape can then be related to the actual bending stress in the rail and estimate the track support through beam theory. Finite element simulations are used to characterize the track response as related to the UNL measurement system. The results of field tests using bondable resistance strain gages illustrate the system’s capability of approximating the actual rail bending stresses under load.