Rajibul Huq

Behavior-modulation technique in mobile robotics using fuzzy discrete event system

This paper presents a novel behavior-modulation technique using a fuzzy discrete event system (FDES) for behavior-based robotic control. The method exploits the multivalued feature of fuzzy logic (FL) and event-driven property of a discrete event system (DES) to generate the activity of a behavior using fuzzy state vectors. State-based prediction of an activity is accomplished using fuzzily defined event matrices. A central arbiter employs priority-based arbitration among the activity state vectors and generates new event matrices to modify the activity states of the behaviors. The method combines aspects of both command fusion and behavior arbitration. Furthermore, the proposed approach has the ability to define state-based observability and controllability to handle sensory uncertainty and environmental dynamics. Observability describes decision vagueness associated with sensory data, whereas controllability specifies undesirable state-reach within the observed environment. Real-time results of FDES-based mobile robot navigation are presented and compared against four different modulation methods to validate its superior performance

The development of an adaptive upper-limb stroke rehabilitation robotic system

BackgroundStroke is the primary cause of adult disability. To support this large population in recovery, robotic technologies are being developed to assist in the delivery of rehabilitation. This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The system uses a decision theoretic model (a partially observable Markov decision process, or POMDP) as its primary engine for decision making. The POMDP allows the system to automatically modify exercise parameters to account for the specific needs and abilities of different individuals, and to use these parameters to take appropriate decisions about stroke rehabilitation exercises.MethodsThe performance of the system was evaluated by comparing the decisions made by the system with those of a human therapist. A single patient participant was paired up with a therapist participant for the duration of the study, for a total of six sessions. Each session was an hour long and occurred three times a week for two weeks. During each session, three steps were followed: (A) after the system made a decision, the therapist either agreed or disagreed with the decision made; (B) the researcher had the device execute the decision made by the therapist; (C) the patient then performed the reaching exercise. These parts were repeated in the order of A-B-C until the end of the session. Qualitative and quantitative question were asked at the end of each session and at the completion of the study for both participants.ResultsOverall, the therapist agreed with the system decisions approximately 65% of the time. In general, the therapist thought the system decisions were believable and could envision this system being used in both a clinical and home setting. The patient was satisfied with the system and would use this system as his/her primary method of rehabilitation.ConclusionsThe data collected in this study can only be used to provide insight into the performance of the system since the sample size was limited. The next stage for this project is to test the system with a larger sample size to obtain significant results.

Mobile robot navigation using motor schema and fuzzy context dependent behavior modulation

This paper presents a novel technique to autonomously select different motor schemas using fuzzy context dependant blending of robot behaviors for navigation. First, a set of motor schemas is formed as behaviors. Both strategic and reactive type schemas have been employed in order to facilitate both the aspects of global and local motion planning. While strategic schemas are formed using the prior knowledge of the environment, the reactive schemas are activated using current sensory data of the robot. For global path planning, a safe path is first created using a Voronoi diagram. For local planning, the Voronoi vertices are treated as immediate subgoals and are used to form schemas leading to achieve optimized traveled distance and goal oriented robot navigation. Two motor schemas are formed as reactive behaviors for obstacle avoidance. The unknown obstacles are modeled using the sensory data. The coordinated behavior is achieved while employing weighed vector summation of the schemas. The adaptation of weights are achieved through a fuzzy inference system where fuzzy rules are used to dynamically generate the weights during navigation. A novel approach is proposed for fuzzy context-dependent blending of schemas. Fuzzy rules are formed using two main criteria into account: the first criterion reasons out the context dependent activity of a schema for achieving goal and the second criterion reasons out cooperative activity of strategic schemas with high priority reactive schemas. Comprehensive results validate that the proposed technique eliminates the existing drawbacks of motor schema approaches available in literature and provides collision free goal oriented robot navigation.

Development of a robotic device for upper limb stroke rehabilitation: A user-centered design approach

Stroke is one of the major causes of permanent adult disability. Stroke frequently affects motor control of the arm, leading to diffculties in doing activities of daily living. This research focuses on developing an upper limb rehabilitation robotic prototype through user-centered design to aid stroke survivors in rehabilitating their arm. To gather requirements from end users, stroke therapy sessions were observed and a survey of stroke therapists was conducted. End user requirements were evaluated to determine technical targets for the mechanical design of the prototype. Evaluation of the prototype was done with stroke therapists in a focus group and a preliminary biomechanical study. As user-centered design would require more iterations of design, testing and evaluation, this project reports a first step in developing an affordable, portable device, which could increase access to stroke rehabilitation for the arm.

Distributed fuzzy discrete event system for robotic sensory information processing

Abstract: This paper presents a novel intelligent sensory information processing technique using a fuzzy discrete event system (FDES) for robotic control. The proposed method combines the predictive control approach of a discrete event system with the approximate reasoning aspect of fuzzy logic. It develops a supervisory control strategy for behavior-based robotic control using distributed FDES. The application of distributed FDES eliminates the formation of complex fuzzy predicates and a large fuzzy rule-base. The FDES-based approach also provides means for analyzing behavior-based decision-making using the observability and controllability of an FDES. The observability of an FDES describes uncertainties in sensory data, and the controllability of an FDES exploits uncertain state transitions in a dynamic environment. Comprehensive experiments on behavior-based mobile robot navigation are presented to authenticate the performance of the proposed methodology.

Performance of daily activities by older adults with dementia: The role of an assistive robot

Older adults with cognitive impairment often have difficulties in remembering the proper sequence of activities of daily living (ADLs) or how to use the tools necessary to perform ADLs. They, therefore, require reminders in a timely fashion while performing ADLs. This is a very stressful situation for the caregivers of people with dementia. In this paper we describe a pilot study where a tele-operated assistive robot helps a group of older adults with dementia (OAwD) to perform an ADL, namely making a cup of tea in the kitchen. Five OAwD along with their caregivers participated in this study which took place in a simulated-home setting. The purpose of this study was to investigate the feasibility and usability of a robotic system in assisting the OAwD to perform ADL in a home setting. The findings from this study will contribute to achieve our ultimate goal of designing a full-fledged assistive robot that assists OAwD aging in their own homes. The assistive robots designed for people with dementia mostly focus on companionship. This is, to the best of our knowledge, the first attempt to design an assistive robot which will provide step-by-step guidance to people with dementia in their activities of daily living.

Robots to assist daily activities: views of older adults with Alzheimer's disease and their caregivers.

BACKGROUND Robots have the potential to both enable older adults with dementia to perform daily activities with greater independence, and provide support to caregivers. This study explored perspectives of older adults with Alzheimers disease (AD) and their caregivers on robots that provide stepwise prompting to complete activities in the home. METHODS Ten dyads participated: Older adults with mild-to-moderate AD and difficulty completing activity steps, and their family caregivers. Older adults were prompted by a tele-operated robot to wash their hands in the bathroom and make a cup of tea in the kitchen. Caregivers observed interactions. Semi-structured interviews were conducted individually. Transcribed interviews were thematically analyzed. RESULTS Three themes summarized responses to robot interactions: contemplating a future with assistive robots, considering opportunities with assistive robots, and reflecting on implications for social relationships. Older adults expressed opportunities for robots to help in daily activities, were open to the idea of robotic assistance, but did not want a robot. Caregivers identified numerous opportunities and were more open to robots. Several wanted a robot, if available. Positive consequences of robots in caregiving scenarios could include decreased frustration, stress, and relationship strain, and increased social interaction via the robot. A negative consequence could be decreased interaction with caregivers. CONCLUSIONS Few studies have investigated in-depth perspectives of older adults with dementia and their caregivers following direct interaction with an assistive prompting robot. To fulfill the potential of robots, continued dialogue between users and developers, and consideration of robot design and caregiving relationship factors are necessary.

QBOT: An educational mobile robot controlled in MATLAB Simulink environment

This paper describes Quansers Mobile Robot Control Framework (QMRCF) for an educational robot called Qbot. The QMRCF accelerates the development of mobile robot control algorithms and hardware-in-the-loop (HIL) testing using model-based design techniques of MATLAB Simulink. This paper also validates the performance of QMRCF using several experiments in various research fields of mobile robotics, e.g., teleoperation, navigation, and obstacle avoidance.

A decision-theoretic approach in the design of an adaptive upper-limb stroke rehabilitation robot

This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The system uses a partially observable Markov decision process (POMDP) as its primary engine for decision-making. The POMDP allows the system to automatically modify exercise parameters to account for the specific needs and abilities of different individuals, and to use these parameters to take appropriate decisions about stroke rehabilitation exercises. The performance of the system was evaluated through various simulations and by comparing the decisions made by the system with those of a human therapist for a single patient. In general, the simulations showed promising results and the therapist thought the system decisions were believable.

Development of a fuzzy logic based intelligent system for autonomous guidance of post-stroke rehabilitation exercise

This paper presents preliminary studies in developing a fuzzy logic based intelligent system for autonomous post-stroke upper-limb rehabilitation exercise. The intelligent system autonomously varies control parameters to generate different haptic effects on the robotic device. The robotic device is able to apply both resistive and assistive forces for guiding the patient during the exercise. The fuzzy logic based decision-making system estimates muscle fatigue of the patient using exercise performance and generates a combination of resistive and assistive forces so that the stroke survivor can exercise for longer durations with increasing control. The fuzzy logic based system is initially developed using a study with healthy subjects and preliminary results are also presented to validate the developed system with healthy subjects. The next stage of this work will collect data from stroke survivors for further development of the system.