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

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

LIBRARIES

b

Hybrid Aerial and Terrestrial Vehicle

A vehicle capable of both aerial and terrestrial locomotion. The terrestrial and aerial vehicle includes a flying device and a rolling cage connected to the flying device by at least one revolute joint. The rolling cage at least partially surrounds the flying device and is free-rolling and is not separately powered.Sponsorship: Illinois Institute of TechnologyUnited States Paten

Hybrid Aerial and Terrestrial Vehicle

A vehicle capable of both aerial and terrestrial locomotion. The terrestrial and aerial vehicle includes a flying device and a rolling cage connected to the flying device by at least one revolute joint. The rolling cage at least partially surrounds the flying device and is free-rolling and not separately powered.Sponsorship: Illinois Institute of TechnologyUnited States Paten

High Speed Hazard Avoidance for Mobile Robots

Mobile robots have important applications in high speed, rough-terrain scenarios. In these scenarios, unexpected and hazardous situations can occur that require rapid hazard avoidance maneuvers. At high speeds, there is limited time to perform re-planning 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 paper presents a method for high speed hazard avoidance. The method is based on the concept of the trajectory space, which is a compact model-based representation of a robot’s dynamic performance limits in uneven, natural terrain. A Monte Carlo method for analyzing system performance despite model parameter uncertainty is briefly presented, and its integration with the trajectory space is discussed. Simulation results for the hazard avoidance algorithm are presented and demonstrate the effectiveness of the method

Fault-Free Integrity of Urban Driverless Vehicle Navigation with Multi-Sensor Integration: A Case Study in Downtown Chicago

This paper investigates how global navigation satellite systems (GNSSs) and inertial navigation systems (INSs), when appropriately augmented by ranging from local landmarks, can safely navigate vehicles through a real-world urban environment. We begin by considering safety requirements for driverless vehicles under fault-free assumptions and developing measurement models for multi-sensor integrated navigation systems using an extended Kalman filter. The critical elements of urban navigation are then discussed, including individual INS noise parameter specifications, vehicle speed, and the effect of velocity updates. Covariance analyses performed along a 9-km-long urban transect in downtown Chicago show that velocity updates measured by wheel speed sensors, vehicle kinematic constraints, and zero-velocity updates can extend navigation continuity by bridging intermittent GNSS signal availability. However, position reference updates at intervals between 15 and 35 m, based on light detection and ranging data from local landmarks in our case, are needed to achieve full navigation availability through the transect

Experimental Study of High-speed Rough-terrain Mobile Robot Models for Reactive Behaviors

High-speed mobile robots have many important applications in rough terrain. At high speeds, it is difficult to guarantee safe robot motion using traditional control and planning techniques. This paper presents an experimental high-speed rover system for studying reactive behavior control to avoid potentially dangerous situations. The method consists of sensor-triggered maneuvers that have been shown by a priori model-based analysis to be safe. The paper discusses vehicle and terrain models for model-based analysis. Experimental results show that behaviors based on detailed models can accurately predict the dynamics of mobile robots in rough terrain.