A simple upper limb rehabilitation trainer

Stroke is a leading cause of disability which can affect shoulder and elbow movements which are necessary for reaching activities in numerous daily routines. To maximize functional recovery of these movements, stroke survivors undergo rehabilitation sessions under the supervision of physiotherapists in healthcare settings. Unfortunately, these sessions may be limited due to staff constraints and are often labor-intensive. There are numerous robotic devices which have been developed to overcome this problem. However, the high cost of these robots is a major concern as it limits their cost-benefit profiles, thus impeding large scale implementation. This paper presents a simple and low cost interactive training module for the purpose of upper limb rehabilitation. The module, which uses a conventional mouse integrated with a small DC motor to generate vibration instead of any robotic actuator, is integrated with a game-like virtual reality system intended for training shoulder and elbow movements. Three games for the module were developed as training platforms, namely: Triangle, Square and Circle games. Results from five healthy study subjects showed that their performances improved with practice and time taken to complete the Triangle game was the fastest of the three

Learned and Controlled Autonomous Robotic Exploration in an Extreme, Unknown Environment

Exploring and traversing extreme terrain with surface robots is difficult, but highly desirable for many applications, including exploration of planetary surfaces, search and rescue, among others. For these applications, to ensure the robot can predictably locomote, the interaction between the terrain and vehicle, terramechanics, must be incorporated into the model of the robot's locomotion. Modeling terramechanic effects is difficult and may be impossible in situations where the terrain is not known a priori. For these reasons, learning a terramechanics model online is desirable to increase the predictability of the robot's motion. A problem with previous implementations of learning algorithms is that the terramechanics model and corresponding generated control policies are not easily interpretable or extensible. If the models were of interpretable form, designers could use the learned models to inform vehicle and/or control design changes to refine the robot architecture for future applications. This paper explores a new method for learning a terramechanics model and a control policy using a model-based genetic algorithm. The proposed method yields an interpretable model, which can be analyzed using preexisting analysis methods. The paper provides simulation results that show for a practical application, the genetic algorithm performance is approximately equal to the performance of a state-of-the-art neural network approach, which does not provide an easily interpretable model.Comment: Published in: 2019 IEEE Aerospace Conference Date of Conference: 2-9 March 2019 Date Added to IEEE Xplore: 20 June 201

An overview of waste materials for sustainable road construction

Untreated soil typically has low shear strength, swelling behavior, high compressibility and its characteristics were highly dependent on the environment. In general, such problematic soil will lead to severe damages in road construction industry such as bearing capacity failure, slope instability, and excessive settlement. Agricultural waste, construction waste, and municipal waste have recently gained considerable attention as a sustainable material in road construction application due to its availability, environmental friendly and low-cost materials. Therefore in this review, randomly distributed fiber reinforced soil and oriented distributed fiber reinforced soil will be extensively discussed based on the emerging trend. It further reviewed the feasibility of using waste materials as a reinforcement material for the road construction industry. The review also attempts to evaluate and compare the engineering properties of soil and sustainable materials in order to enhance soil performance as well as help to improve the environment affected by growing waste materials

Contact aware robust semi-autonomous teleoperation of mobile manipulators

In the context of human-robot collaboration, cooperation and teaming, the use of mobile manipulators is widespread on applications involving unpredictable or hazardous environments for humans operators, like space operations, waste management and search and rescue on disaster scenarios. Applications where the manipulator's motion is controlled remotely by specialized operators. Teleoperation of manipulators is not a straightforward task, and in many practical cases represent a common source of failures. Common issues during the remote control of manipulators are: increasing control complexity with respect the mechanical degrees of freedom; inadequate or incomplete feedback to the user (i.e. limited visualization or knowledge of the environment); predefined motion directives may be incompatible with constraints or obstacles imposed by the environment. In the latter case, part of the manipulator may get trapped or blocked by some obstacle in the environment, failure that cannot be easily detected, isolated nor counteracted remotely. While control complexity can be reduced by the introduction of motion directives or by abstraction of the robot motion, the real-time constraint of the teleoperation task requires the transfer of the least possible amount of data over the system's network, thus limiting the number of physical sensors that can be used to model the environment. Therefore, it is of fundamental to define alternative perceptive strategies to accurately characterize different interaction with the environment without relying on specific sensory technologies. In this work, we present a novel approach for safe teleoperation, that takes advantage of model based proprioceptive measurement of the robot dynamics to robustly identify unexpected collisions or contact events with the environment. Each identified collision is translated on-the-fly into a set of local motion constraints, allowing the exploitation of the system redundancies for the computation of intelligent control laws for automatic reaction, without requiring human intervention and minimizing the disturbance of the task execution (or, equivalently, the operator efforts). More precisely, the described system consist in two different building blocks. The first, for detecting unexpected interactions with the environment (perceptive block). The second, for intelligent and autonomous reaction after the stimulus (control block). The perceptive block is responsible of the contact event identification. In short, the approach is based on the claim that a sensorless collision detection method for robot manipulators can be extended to the field of mobile manipulators, by embedding it within a statistical learning framework. The control deals with the intelligent and autonomous reaction after the contact or impact with the environment occurs, and consist on an motion abstraction controller with a prioritized set of constrains, where the highest priority correspond to the robot reconfiguration after a collision is detected; when all related dynamical effects have been compensated, the controller switch again to the basic control mode

Otimização de locomoção bípede

Dissertação de mestrado integrado em Engenharia BiomédicaAtualmente verifica-se um crescimento exponencial a nível de desenvolvimento de sistemas robóticos móveis havendo um esforço para criar sistemas com propriedades mais eficientes e adaptáveis às exigências do ambiente de trabalho. Neste contexto, têm havido uma preocupação acrescida em desenvolver melhores sistemas de locomoção quer seja locomoção por rodas quer seja por pernas (bípede, quadrúpede e hexapode). Esta dissertação foca-se na otimização da locomoção bípede a qual é uma área que tem sido alvo de grande atenção uma vez que esta é uma área da robótica que ainda necessita de progredir no sentido de conseguir finalmente uma locomoção tão eficiente como a marcha humana. Deste modo, a elaboração deste trabalho teve como objetivos principais a criação de uma estratégia de otimização que combinasse a geração de padrões de movimento através de geradores centrais de padrões (CPGs) com um algoritmo de otimização evolucionário (Non-Dominated Sorting Genetic Algorithm ll). Essa estratégia implicou a determinação de objetivos que correspondem a características da locomoção bípede e que foram otimizados, sendo eles o deslocamento frontal, a altura a que o pé levanta, a força de impacto entre os pés e o chão e a posição do centro de massa. Os resultados foram obtidos a partir de simulações na plataforma Webots para o robô bípede Darwin-OP. Neste contexto, os resultados foram muito satisfatórios uma vez que o algoritmo foi capaz de gerar locomoção estável e os objetivos propostos foram otimizados. Foi feito também um estudo de sensibilidade que determinou a existência de parâmetros de CPGs que apresentam uma forte correlação positiva com as funções objetivos. Assim, os parâmetros Acompasso, frequência ω e ORoll influenciam fortemente o deslocamento e a força de impacto e o parâmetro AhPitch influencia a altura a que o pé levanta. No futuro seria pertinente aplicar o algoritmo elaborado num robô bípede real e conferir se consegue gerar uma locomoção eficiente em condições reais.Presently there is an exponential increase on the level of development of mobile robotic systems and so there is an effort to create systems with properties more efficient and adaptable to the demands of the work environment. In this context, there has been a heightened concern in developing better systems of locomotion either by wheels either by legs (bipedal, 4-legged or 6-legged). This dissertation focuses on the optimization of bipedal locomotion which is an area that has been the subject of much attention since this is an area of robotics that still needs to make progress towards finally achieving locomotion as efficient as the human gait. Thus, this work aimed to create an optimization strategy that combines the generation of movement patterns through central pattern generators (CPGs) with an evolutionary optimization algorithm (Non-Dominated Sorting Genetic Algorithm II). This strategy involved the determination of objectives that correspond to characteristics of bipedal locomotion and that have been optimized, namely the frontal displacement, the ground clearance, the impact force between the foot and the ground and the position of the center of mass. The results were obtained from simulations in Webots platform for the bipedal robot Darwin-OP. The results were very satisfactory since the algorithm was able to generate stable locomotion and the proposed objectives were optimized. We also made a sensitivity analysis that determined the existence of CPGs parameters that exhibit a strong positive correlation with the objective functions. Thus, the parameters Acompasso, the frequency ω and ORoll strongly influence the impact force and displacement as well as AhPitch influences the height to which the foot rises. In the future it would be appropriate to apply the developed algorithm in a real biped robot and check if it can generate an efficient locomotion in real conditions

Locomotion system for ground mobile robots in uneven and unstructured environments

One of the technology domains with the greatest growth rates nowadays is service robots. The extensive use of ground mobile robots in environments that are unstructured or structured for humans is a promising challenge for the coming years, even though Automated Guided Vehicles (AGV) moving on flat and compact grounds are already commercially available and widely utilized to move components and products inside indoor industrial buildings. Agriculture, planetary exploration, military operations, demining, intervention in case of terrorist attacks, surveillance, and reconnaissance in hazardous conditions are important application domains. Due to the fact that it integrates the disciplines of locomotion, vision, cognition, and navigation, the design of a ground mobile robot is extremely interdisciplinary. In terms of mechanics, ground mobile robots, with the exception of those designed for particular surroundings and surfaces (such as slithering or sticky robots), can move on wheels (W), legs (L), tracks (T), or hybrids of these concepts (LW, LT, WT, LWT). In terms of maximum speed, obstacle crossing ability, step/stair climbing ability, slope climbing ability, walking capability on soft terrain, walking capability on uneven terrain, energy efficiency, mechanical complexity, control complexity, and technology readiness, a systematic comparison of these locomotion systems is provided in [1]. Based on the above-mentioned classification, in this thesis, we first introduce a small-scale hybrid locomotion robot for surveillance and inspection, WheTLHLoc, with two tracks, two revolving legs, two active wheels, and two passive omni wheels. The robot can move in several different ways, including using wheels on the flat, compact ground,[1] tracks on soft, yielding terrain, and a combination of tracks, legs, and wheels to navigate obstacles. In particular, static stability and non-slipping characteristics are considered while analyzing the process of climbing steps and stairs. The experimental test on the first prototype has proven the planned climbing maneuver’s efficacy and the WheTLHLoc robot's operational flexibility. Later we present another development of WheTLHLoc and introduce WheTLHLoc 2.0 with newly designed legs, enabling the robot to deal with bigger obstacles. Subsequently, a single-track bio-inspired ground mobile robot's conceptual and embodiment designs are presented. This robot is called SnakeTrack. It is designed for surveillance and inspection activities in unstructured environments with constrained areas. The vertebral column has two end modules and a variable number of vertebrae linked by compliant joints, and the surrounding track is its essential component. Four motors drive the robot: two control the track motion and two regulate the lateral flexion of the vertebral column for steering. The compliant joints enable limited passive torsion and retroflection of the vertebral column, which the robot can use to adapt to uneven terrain and increase traction. Eventually, the new version of SnakeTrack, called 'Porcospino', is introduced with the aim of allowing the robot to move in a wider variety of terrains. The novelty of this thesis lies in the development and presentation of three novel designs of small-scale mobile robots for surveillance and inspection in unstructured environments, and they employ hybrid locomotion systems that allow them to traverse a variety of terrains, including soft, yielding terrain and high obstacles. This thesis contributes to the field of mobile robotics by introducing new design concepts for hybrid locomotion systems that enable robots to navigate challenging environments. The robots presented in this thesis employ modular designs that allow their lengths to be adapted to suit specific tasks, and they are capable of restoring their correct position after falling over, making them highly adaptable and versatile. Furthermore, this thesis presents a detailed analysis of the robots' capabilities, including their step-climbing and motion planning abilities. In this thesis we also discuss possible refinements for the robots' designs to improve their performance and reliability. Overall, this thesis's contributions lie in the design and development of innovative mobile robots that address the challenges of surveillance and inspection in unstructured environments, and the analysis and evaluation of these robots' capabilities. The research presented in this thesis provides a foundation for further work in this field, and it may be of interest to researchers and practitioners in the areas of robotics, automation, and inspection. As a general note, the first robot, WheTLHLoc, is a hybrid locomotion robot capable of combining tracked locomotion on soft terrains, wheeled locomotion on flat and compact grounds, and high obstacle crossing capability. The second robot, SnakeTrack, is a small-size mono-track robot with a modular structure composed of a vertebral column and a single peripherical track revolving around it. The third robot, Porcospino, is an evolution of SnakeTrack and includes flexible spines on the track modules for improved traction on uneven but firm terrains, and refinements of the shape of the track guidance system. This thesis provides detailed descriptions of the design and prototyping of these robots and presents analytical and experimental results to verify their capabilities

FLUX-PINNED DYNAMICAL SYSTEMS WITH APPLICATION TO SPACEFLIGHT

Technology enables space exploration and scientific discovery. At this amazing intersection of time, new software and hardware capabilities give rise to daring robotic exploration and autonomy. Close-proximity operations for spacecraft is a particularly critical portion of any robotic mission that enables many types of maneuvers, such as docking and capture, formation flying, and on-orbit assembly. These dynamic maneuvers then enable different missions, like sample return, spacecraft construction larger than a single rocket faring, and deep-space operations. Commonly, spacecraft dynamic control uses thrusters for position and attitude control, which rely on active sensing and consumable propellant. The development of other dynamic control techniques opens new capabilities and system advantages, and further offers a more diverse technological trade space for system optimization. This research comprehensively investigates the utilization of flux-pinning physics to manipulate spacecraft dynamics. Flux-pinned interfaces differ from conventional dynamic control through its passive and compliant behavior. These unique characteristics are extremely attractive for certain applications, but flux-pinned technology must mature considerably before adoption for spaceflight missions. A dynamic capture and docking maneuver in an upcoming mission concept, Mars Sample Return, motivates the technology design. This body of work as much as possible follows a progression from cradle to grave. A flux-pinning theoretical dynamics model and a system architecture are presented to specify general capabilities of such a spacecraft system. Different analyses on stability, state sensitivity, backwards reachability result from a physics-based dynamics model. An extensive literature review and basic science experiments inform a theoretical dynamics model about the incorporation of physical parameters when simulating realistic dynamics. A series of testbeds enable experimentation and precise investigation of flux-pinned interface capabilities in the context of docking and capture. The testbeds ranged from the simplest expression of dynamics, in a single degree of freedom, to a flight traceable expression, in all six degrees of freedom. Experiments from these testbeds define and characterize system level capabilities specific to flux-pinned capture. Data collected from these experiments then supports development of a predictive dynamics model of the hardware system. Various system identification methods aid in creating a dynamics model that accurately predicts the dynamics observed during experiments. Several objective metrics are considered to evaluate the model fidelity. The types of system identification methods are separated into analytical methods and numerical methods. The analytical method involves parameter estimation in a physics-based model. Numerical methods involve Taylor expansion, bag of functions, symbolic regression, and neural networks. Theoretical extensions towards verification further develops neural network approximation methods, driving at safe, real-time system identification