SmartWalker, a mobility aid for the elderly

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (leaves 81-82).In the near future, the baby boomer population will cause a growth in the number of people entering nursing homes. Currently, if people wish to stay out of a nursing home, they must hire a personal aid to take care of daily tasks. A more cost-effective method could be to employ a robotic aid to help with these chores. One such aid is the SmartWalker, a robotic device that would provide health-monitoring sensors, physical support, and help in mobility to the elderly. The focus of this thesis is the design and analysis of the SmartWalker hardware. The design tools necessary to prevent the SmartWalker from slipping, tipping over, and experiencing brake failure are presented. Furthermore, a study of the omnidirectional platform used on the SmartWalker is performed for uneven terrain. It is shown that all of the wheels of the platform touch the ground at the same time. A simulation of a split caster mobility module, the main component of the omnidirectional platform, traversing a bump is also done. This proves that the control algorithms designed for a perfectly flat floor will suffice on an uneven floor. In addition, this thesis discusses the mechanical design that is necessary to build the SmartWalker. The mechanical design focuses on the split caster mobility modules, the slip rings, the frame, and the tradeoffs between strength and weight.by Matthew J. Spenko.S.M

Hazard avoidance for high-speed rough-terrain unmanned ground vehicles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005."June 2005."Includes bibliographical references (p. 111-116).High-speed unmanned ground vehicles have important applications in rough-terrain. In these applications unexpected and dangerous situations can occur that require rapid hazard avoidance maneuvers. At high speeds, there is limited time to perform navigation and hazard avoidance calculations based on detailed vehicle and terrain models. Furthermore, detailed models often do not accurately predict the robot's performance due to model parameter and sensor uncertainty. This thesis presents the development and analysis of a novel method for high speed navigation and hazard avoidance. The method is based on the two dimensional "trajectory space," which is a compact model-based representation of a robot's dynamic performance limits on natural terrain. This method allows a vehicle to perform dynamically feasible hazard avoidance maneuvers in a computationally efficient manner. This thesis also presents a novel method for trajectory replanning, based on a "curvature matching" technique. This method quickly generates a path connects the end of the path generated by a hazard avoidance maneuver to the nominal desired path. Simulation and experimental results with a small gasoline-powered high-speed unmanned ground vehicle verify the effectiveness of these algorithms. The experimental results demonstrate the ability of the algorithm to account for multiple hazards, varying terrain inclination, and terrain roughness. The experimental vehicle attained speeds of 8 m/s (18 mph) on flat and sloped terrain and 7 m/s (16 mph) on rough terrain.by Matthew J. Spenko.Ph.D

Biologically Inspired Climbing with a Hexapedal Robot

This paper presents an integrated, systems-level view of several novel design and control features associated with the biologically inspired, hexapedal, RiSE (Robots in Scansorial Environments) robot. RiSE is the first legged machine capable of locomotion on both the ground and a variety of vertical building surfaces including brick, stucco, and crushed stone at speeds up to 4 cm/s, quietly and without the use of suction, magnets, or adhesives. It achieves these capabilities through a combination of bioinspired and traditional design methods. This paper describes the design process and specifically addresses body morphology, hierarchical compliance in the legs and feet, and sensing and control systems that enable robust and reliable climbing on difficult surfaces. Experimental results illustrate the effects of various behaviors on climbing performance and demonstrate the robot\u27s ability to climb reliably for long distances

Extending our scientific reach in arboreal ecosystems for research and management

The arboreal ecosystem is vitally important to global and local biogeochemical processes, the maintenance of biodiversity in natural systems, and human health in urban environments. The ability to collect samples, observations, and data to conduct meaningful scientific research is similarly vital. The primary methods and modes of access remain limited and difficult. In an online survey, canopy researchers (n = 219) reported a range of challenges in obtaining adequate samples, including ∼10% who found it impossible to procure what they needed. Currently, these samples are collected using a combination of four primary methods: (1) sampling from the ground; (2) tree climbing; (3) constructing fixed infrastructure; and (4) using mobile aerial platforms, primarily rotorcraft drones. An important distinction between instantaneous and continuous sampling was identified, allowing more targeted engineering and development strategies. The combination of methods for sampling the arboreal ecosystem provides a range of possibilities and opportunities, particularly in the context of the rapid development of robotics and other engineering advances. In this study, we aim to identify the strategies that would provide the benefits to a broad range of scientists, arborists, and professional climbers and facilitate basic discovery and applied management. Priorities for advancing these efforts are (1) to expand participation, both geographically and professionally; (2) to define 2–3 common needs across the community; (3) to form and motivate focal teams of biologists, tree professionals, and engineers in the development of solutions to these needs; and (4) to establish multidisciplinary communication platforms to share information about innovations and opportunities for studying arboreal ecosystems

The Parametrized Extrapolator

This study is focused on fast track extrapolations in the magnetic field of the LHCb detector setup. The magnetic field map is discussed and visualized. Already implemented extrapolators are analyzed briefly. The main focus of the study is the new "Parametrized Extrapolator", that was proposed by prof. Pierre Billoir. The extrapolator concept and functioning are presented in detail. The performance of this parametrized extrapolator is studied in terms of deviations when compared to a reference extrapolator. In the end future improvements and ideas are discussed

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