Terrain

Innate Terrain surveys landscape architecture from across Canada, documenting the inspiring breadth of contemporary projects.

Founded in a historic nursery in southeast Pennsylvania, Terrain is a nationally renowned garden, home, and lifestyle brand with an entirely fresh approach to living with nature. It’s an approach that bridges the gap between home and garden, the indoors and the outdoors. An approach that embraces decorating with plants and inviting the garden into every living space. Terrain, the book, not only captures the brand’s unique and lushly appealing sensibility in over 450 beautiful photographs but also shows, in project after project, tip after tip, how to live with nature at home. Here are ideas for flower arranging beyond the expected bouquet, using branches and wild blooms, seed heads and bulbs. Ten colorful container gardens inspired by painterly palettes. Dozens of ideas for making wreaths out of vines, dried stems, evergreens, and fresh leaves and fern fronds (which you learn to preserve in glycerin). Here are secrets for forcing branches to bloom in the middle of winter. Decorating with heirloom pumpkins, including turning them into tabletop planters. Simple touches—like massing high-summer hydrangeas into weathered baskets and scattering them around the patio—and more involved projects, including taking inspiration from Scandinavia and Britain to create a truly natural Christmas. With inspiration for every season, Terrain blurs the indoors and out to bring the subtle and surprising joys of nature into our lives every day.

How-to-Guide of making wargame terrain

This monograph discusses issues related to estimation, control, and motion planning for mobile robots operating in rough terrain, with particular attention to planetary exploration rovers. Rough terrain robotics is becoming increasingly important in space exploration, and industrial applications. However, most current motion planning and control algorithms are not well suited to rough terrain mobility, since they do not consider the physical characteristics of the rover and its environment. Specific addressed topics are: wheel terrain interaction modeling, including terrain parameter estimation and wheel terrain contact angle estimation; rough terrain motion planning; articulated suspension control; and traction control. Simulation and experimental results are presented that show that the desribed algorithms lead to improved mobility for robotic systems in rough terrain.

Dynamic modeling is the fundamental building block for mechanism analysis, design, control and performance evaluation. One class of mechanism, legged machines, have multiple closed-chains established through intermittent ground contacts. Further, walking on natural terrain introduces nonlinear system compliance in the forms of foot sinkage and slippage. Closed-chains constrain the possible motions of a mechanism while compliances affect the redistribution of forces throughout the system. A General Model of Legged Locomotion on Natural Terrain develops a dynamic mechanism model that characterizes indeterminate interactions of a closed-chain robot with its environment. The approach is applicable to any closed-chain mechanism with sufficient contact compliance, although legged locomotion on natural terrain is chosen to illustrate the methodology. The modeling and solution procedures are general to all walking machine configurations, including bipeds, quadrupeds, beam-walkers and hopping machines. This work develops a functional model of legged locomotion that incorporates, for the first time, non-conservative foot-soil interactions in a nonlinear dynamic formulation. The model was applied to a prototype walking machine, and simulations generated significant insights into walking machine performance on natural terrain. The simulations are original and essential contributions to the design, evaluation and control of these complex robot systems. While posed in the context of walking machines, the approach has wider applicability to rolling locomotors, cooperating manipulators, multi-fingered hands, and prehensile agents.

Digital Terrain Analysis in Soil Science and Geology provides soil scientists and geologists with an integrated view of the principles and methods of digital terrain analysis. Its attention to first principles and focus on error analysis makes it a useful resource for scientists to uncover the method applications particular to their needs. Digital Terrain Analysis in Soil Science and Geology covers a wide range of applications in the context of multi-scale problems of soil science and geology. Presents a mathematical approach from a single author who is actively researching in the field and has published a number of fundamental papers Outlines principles and methods and then follows with examples in a simple setup that builds on content Provides an integrated view of the principles and methods of digital terrain analysis

Terrain Relative Navigation (TRN) provides bounded-error localization relative to an environment by matching range measurements of local terrain against an a priori map. The environment-relative and onboard sensing characteristics of TRN make it a powerful tool for return-to-site missions in GPS-denied environments, with potential applications ranging from underwater and space robotic exploration to pedestrian indoor navigation. For many of these applications, available sensors may be limited by mission power/weight constraints, cost restrictions, and environmental effects (e.g. inability to use a magnetic compass in space). Such limitations not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ TRN. Consequently, despite numerous advances in TRN technology over the past several decades, the application of TRN has been restricted to systems with highly accurate and information-rich sensor systems. In addition, a limited understanding of the effects of map quality and sensor quality on TRN performance has overly restricted the types of missions for which TRN has been considered a viable navigation solution. This thesis develops two new capabilities for TRN methods, resulting in significantly increased TRN applicability. First, a tightly-coupled filtering framework is developed which enables the successful use of TRN on vehicles with both low-accuracy navigation sensors and simple, low-information range sensors. This new filtering framework has similarities to tightly-coupled integration methods for GPS-aided navigation systems. Second, a set of analysis and design tools based on the Posterior Cramer-Rao Lower Bound are developed which allow for reliable TRN performance predictions as a function of both sensor and map quality. These analyses include the development of a new terrain map error model based on the variogram which allows for performance prediction as a function of map resolution. These developed capabilities are validated through field demonstrations on Autonomous Underwater Vehicles (AUVs) operated out of the Monterey Bay Aquarium Research Institute (MBARI), where available sensing has been limited primarily by cost. These trials include a real-time, closed-loop demonstration of the developed tightly-coupled TRN framework, enabling 5m accuracy return-to-site on a sensor-limited AUV where traditional TRN methods failed to provide better than 150m accuracy. The results further demonstrate the accurate prediction capability of the developed performance bounds on fielded systems, verifying their utility as design and planning tools for future TRN missions.