Assessing the effectiveness of robot facilitated neurorehabilitation for relearning motor skills following a stroke

A growing awareness of the potential for machine-mediated neurorehabilitation has led to several novel concepts for delivering these therapies. To get from laboratory demonstrators and prototypes to the point where the concepts can be used by clinicians in practice still requires significant additional effort, not least in the requirement to assess and measure the impact of any proposed solution. To be widely accepted a study is required to use validated clinical measures but these tend to be subjective, costly to administer and may be insensitive to the effect of the treatment. Although this situation will not change, there is good reason to consider both clinical and mechanical assessments of recovery. This article outlines the problems in measuring the impact of an intervention and explores the concept of providing more mechanical assessment techniques and ultimately the possibility of combining the assessment process with aspects of the intervention.

Design of a biomimetic skin for an octopus-inspired robot– Part I: characterising octopus skin

Octopus skin samples were tested under quasi-static and scissor cutting conditions to measure the in-plane material properties and fracture toughness. Samples from all eight arms of one octopus were tested statically to investigate how properties vary from arm to arm. Another nine octopus skins were measured to study the influence of body mass on skin properties. Influence of specimen location on skin mechanical properties was also studied. Material properties of skin, i.e. the Young's modulus, ultimate stress, failure strain and fracture toughness have been plotted against the position of skin along the length of arm or body. Statistical studies were carried out to help analyzing experimental data obtained. Results of this work will be used as guidelines for the design and development of artificial skins for an octopus-inspired robot.

Design of a biomimetic skin for an octopus-inspired robot - Part II: Development of the skin artefact

In order to develop skin artefact for an octopus-inspired robot arm, which is designed to be able to elongate 60% of its original length, silicone rubber and knitted nylon sheet were selected to manufacture an artificial skin, due to their higher elastic strain and high flexibility. Tensile and scissors cutting tests were conducted to characterise the matrix and reinforcing materials and the skin artefact. Material properties of the individual and the composite materials were compared with the measured properties of real octopus skin presented in Part I. The Young’s modulus of the skin should be below 20 MPa and the elastic strain range should be over 60%. The fracture toughness should be at least 0.9 kJ·m−2. Tubes made of the skin artefact filled with liquid were tested to study volume change under deformation. Finite element analysis model was developed to simulate the material and arm structure under tensile loading. Results show that the skin artefact developed has similar mechanical properties as the real octopus skin and satisfies all the design specifications of the OCTOPUS robot.

Predictive computed-torque control of a PUMA 560 manipulator robot

This paper describes the integration of constrained predictive control and computed-torque control, and its application on a six degree-of-freedom PUMA 560 manipulator arm. The real-time implementation was based on SIMULINK, with the predictive controller and the computed-torque control law implemented in the C programming language. The constrained predictive controller solved a quadratic programming problem at every sampling interval, which was as short as 10 ms, using a prediction horizon of 150 steps and an 18th order state space model.

Transputer control of a Puma 560 robot via the virtual bus

The robot control problem is discussed with regard to controller implementation on a multitransputer array. Some high-performance aspects required of such controllers are described, with particular reference to robot force control. The implications for the architecture required for controllers based on computed torque are discussed and an example is described. The idea of treating a transputer array as a virtual bus is put forward for the implementation of fast real-time controllers. An example is given of controlling a Puma 560 industrial robot. Some of the practical considerations for using transputers for such control are described.

Chaos in high performance digital robot controllers

Active robot force control requires some form of dynamic inner loop control for stability. The author considers the implementation of position-based inner loop control on an industrial robot fitted with encoders only. It is shown that high gain velocity feedback for such a robot, which is effectively stationary when in contact with a stiff environment, involves problems beyond the usual caveats on the effects of unknown environment stiffness. It is shown that it is possible for the controlled joint to become chaotic at very low velocities if encoder edge timing data are used for velocity measurement. The results obtained indicate that there is a lower limit on controlled velocity when encoders are the only means of joint measurement. This lower limit to speed is determined by the desired amount of loop gain, which is itself determined by the severity of the nonlinearities present in the drive system.

Transputer based real time robot control

A parallel processor architecture based on a communicating sequential processor chip, the transputer, is described. The architecture is easily linearly extensible to enable separate functions to be included in the controller. To demonstrate the power of the resulting controller some experimental results are presented comparing PID and full inverse dynamics on the first three joints of a Puma 560 robot. Also examined are some of the sample rate issues raised by the asynchronous updating of inertial parameters, and the need for full inverse dynamics at every sample interval is questioned.

Developing sensorized arm skin for an octopus inspired robot

Soft skin artefacts made of knitted nylon reinforced silicon rubber were fabricated mimicking octopus skin. A combination of ecoflex 0030 and 0010 were used as matrix of the composite to obtain the right stiffness for the skin artefacts. Material properties were characterised using static uniaxial tension and scissors cutting tests. Two types of tactile sensors were developed to detect normal contact; one used quantum tunnelling composite materials and the second was fabricated from silicone rubber and a conductive textile. Sensitivities of the sensors were tested by applying different modes of loading and the soft sensors were incorporated into the skin prototype. Passive suckers were developed and tested against squid suckers. An integrated skin prototype with embedded deformable sensors and attached suckers developed for the arm of an octopus inspired robot is also presented.

Evaluation of reach and grasp robot-assisted therapy suggests similar functional recovery patterns on proximal and distal arm segments in sub-acute hemiplegia

This paper provides some additional evidence in support of the hypothesis that robot therapies are clinically beneficial in neurorehabilitation. Although only 4 subjects were included in the study, the design of the intervention and the measures were done so as to minimise bias. The results are presented as single case studies, and can only be interpreted as such due to the study size. The intensity of intervention was 16 hours and the therapy philosophy (based on Carr and Shepherd) was that coordinated movements are preferable to joint based therapies, and that coordinating distal movements (in this case grasps) helps not only to recover function in these areas, but has greater value since the results are immediately transferable to daily skills such as reach and grasp movements.

Simulation of a diffusion driven mobile robot

In this paper, we investigate the possibility to control a mobile robot via a sensory-motory coupling utilizing diffusion system. For this purpose, we implemented a simulation of the diffusion process of chemicals and the kinematics of the mobile robot. In comparison to the original Braitenberg vehicle in which sensorymotor coupling is tightly realised by hardwiring, our system employs the soft coupling. The mobile robot has two sets of independent sensory-motor unit, two sensors are implemented in front and two motors on each side of the robot. The framework used for the sensory-motor coupling was such that 1) Place two electrodes in the medium 2) Drop a certain amount of Chemical U and V related to the distance to the walls and the intensity of the light 3) Place other two electrodes in the medium 4) Measure the concentration of Chemical U and V to actuate the motors on both sides of the robot. The environment was constructed with four surrounding walls and a light source located at the center. Depending on the design parameters and initial conditions, the robot was able to successfully avoid the wall and light. More interestingly, the diffusion process in the sensory-motor coupling provided the robot with a simple form of memory which would not have been possible with a control framework based on a hard-wired electric circuit.

Situation assessment through multi-modal sensing of dynamic environments to support cognitive robot control

Awareness of emerging situations in a dynamic operational environment of a robotic assistive device is an essential capability of such a cognitive system, based on its effective and efficient assessment of the prevailing situation. This allows the system to interact with the environment in a sensible (semi)autonomous / pro-active manner without the need for frequent interventions from a supervisor. In this paper, we report a novel generic Situation Assessment Architecture for robotic systems directly assisting humans as developed in the CORBYS project. This paper presents the overall architecture for situation assessment and its application in proof-of-concept Demonstrators as developed and validated within the CORBYS project. These include a robotic human follower and a mobile gait rehabilitation robotic system. We present an overview of the structure and functionality of the Situation Assessment Architecture for robotic systems with results and observations as collected from initial validation on the two CORBYS Demonstrators.

The remote control ofmobile robot on theInternet

During last decades, the Internet teleobotics has been growing at an enormous ratedue to the rapid improvement of Internet technology. This paper presents theinternet-based remote control of mobile robot. To face unpredictable Internet delaysand possible connection rupture, a direct continuous control based teleoperationarchitecture with “Speed Limit Module” (SLM) and “Delay Approximator” (DA) isproposed. This direct continuous control architecture guarantees the path error of therobot motion is restricted within the path error tolerance of the application.Experiment results show the feasibility and effectiveness of this direct Internet controlarchitecture in the real Internet environment.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.