Design of an active arm support for assisting arm movements

In this paper we have explored areas of application for health care manipulators and possible user groups. We have shown the steps in the design approach to the conceptual mechanism from the AAS. The future work will be measurement from properties of the muscle with the elbow parameterization test-bed to get a database to design one part of the control area from the AAS. More work on the mechanical design is required before a functional prototype can be built.

Action observation and robotic agents: learning and anthropomorphism

The ‘action observation network’ (AON), which is thought to translate observed actions into motor codes required for their execution, is biologically tuned: it responds more to observation of human, than non-human, movement. This biological specificity has been taken to support the hypothesis that the AON underlies various social functions, such as theory of mind and action understanding, and that, when it is active during observation of non-human agents like humanoid robots, it is a sign of ascription of human mental states to these agents. This review will outline evidence for biological tuning in the AON, examining the features which generate it, and concluding that there is evidence for tuning to both the form and kinematic profile of observed movements, and little evidence for tuning to belief about stimulus identity. It will propose that a likely reason for biological tuning is that human actions, relative to non-biological movements, have been observed more frequently while executing corresponding actions. If the associative hypothesis of the AON is correct, and the network indeed supports social functioning, sensorimotor experience with non-human agents may help us to predict, and therefore interpret, their movements.

Simplified PID self-tuning controller for robotic manipulators

The paper describes a self-tuning adaptive PID controller suitable for use in the control of robotic manipulators. The scheme employs a simple recursive estimator which reduces the computational effort to an acceptable level for many applications in robotics.

Sensorimotor experience enhances automatic imitation of robotic action

Recent research in cognitive neuroscience has found that observation of human actions activates the ‘mirror system’ and provokes automatic imitation to a greater extent than observation of non-biological movements. The present study investigated whether this human bias depends primarily on phylogenetic or ontogenetic factors by examining the effects of sensorimotor experience on automatic imitation of non-biological robotic, stimuli. Automatic imitation of human and robotic action stimuli was assessed before and after training. During these test sessions, participants were required to execute a pre-specified response (e.g. to open their hand) while observing a human or robotic hand making a compatible (opening) or incompatible (closing) movement. During training, participants executed opening and closing hand actions while observing compatible (group CT) or incompatible movements (group IT) of a robotic hand. Compatible, but not incompatible, training increased automatic imitation of robotic stimuli (speed of responding on compatible trials, compared with incompatible trials) and abolished the human bias observed at pre-test. These findings suggest that the development of the mirror system depends on sensorimotor experience, and that, in our species, it is biased in favour of human action stimuli because these are more abundant than non-biological action stimuli in typical developmental environments.

Bottom-up, not top-down, modulation of imitation by human and robotic models

Visual observation of human actions provokes more motor activation than observation of robotic actions. We investigated the extent to which this visuomotor priming effect is mediated by bottom-up or top-down processing. The bottom-up hypothesis suggests that robotic movements are less effective in activating the ‘mirror system’ via pathways from visual areas via the superior temporal sulcus to parietal and premotor cortices. The top-down hypothesis postulates that beliefs about the animacy of a movement stimulus modulate mirror system activity via descending pathways from areas such as the temporal pole and prefrontal cortex. In an automatic imitation task, subjects performed a prespecified movement (e.g. hand opening) on presentation of a human or robotic hand making a compatible (opening) or incompatible (closing) movement. The speed of responding on compatible trials, compared with incompatible trials, indexed visuomotor priming. In the first experiment, robotic stimuli were constructed by adding a metal and wire ‘wrist’ to a human hand. Questionnaire data indicated that subjects believed these movements to be less animate than those of the human stimuli but the visuomotor priming effects of the human and robotic stimuli did not differ. In the second experiment, when the robotic stimuli were more angular and symmetrical than the human stimuli, human movements elicited more visuomotor priming than the robotic movements. However, the subjects’ beliefs about the animacy of the stimuli did not affect their performance. These results suggest that bottom-up processing is primarily responsible for the visuomotor priming advantage of human stimuli.

Robotic movement elicits automatic imitation

Recent behavioural and neuroimaging studies have found that observation of human movement, but not of robotic movement, gives rise to visuomotor priming. This implies that the 'mirror neuron' or 'action observation–execution matching' system in the premotor and parietal cortices is entirely unresponsive to robotic movement. The present study investigated this hypothesis using an 'automatic imitation' stimulus–response compatibility procedure. Participants were required to perform a prespecified movement (e.g. opening their hand) on presentation of a human or robotic hand in the terminal posture of a compatible movement (opened) or an incompatible movement (closed). Both the human and the robotic stimuli elicited automatic imitation; the prespecified action was initiated faster when it was cued by the compatible movement stimulus than when it was cued by the incompatible movement stimulus. However, even when the human and robotic stimuli were of comparable size, colour and brightness, the human hand had a stronger effect on performance. These results suggest that effector shape is sufficient to allow the action observation–matching system to distinguish human from robotic movement. They also indicate, as one would expect if this system develops through learning, that to varying degrees both human and robotic action can be 'simulated' by the premotor and parietal cortices.

Advances in upper limb stroke rehabilitation: a technology push

Strokes affect thousands of people worldwide leaving sufferers with severe disabilities affecting their daily activities. In recent years, new rehabilitation techniques have emerged such as constraint-induced therapy, biofeedback therapy and robot-aided therapy. In particular, robotic techniques allow precise recording of movements and application of forces to the affected limb, making it a valuable tool for motor rehabilitation. In addition, robot-aided therapy can utilise visual cues conveyed on a computer screen to convert repetitive movement practice into an engaging task such as a game. Visual cues can also be used to control the information sent to the patient about exercise performance and to potentially address psychosomatic variables influencing therapy. This paper overviews the current state-of-the-art on upper limb robot-mediated therapy with a focal point on the technical requirements of robotic therapy devices leading to the development of upper limb rehabilitation techniques that facilitate reach-to-touch, fine motor control, whole-arm movements and promote rehabilitation beyond hospital stay. The reviewed literature suggest that while there is evidence supporting the use of this technology to reduce functional impairment, besides the technological push, the challenge ahead lies on provision of effective assessment of outcome and modalities that have a stronger impact transferring functional gains into functional independence.

Consumer robotic products: studying the factors that influence market adoption

The aim of this article is to identify the key factors that are associated with the adoption of a commercial robot in the home. This article is based on the development of the robot product Cybot by the University of Reading in conjunction with a publisher (Eaglemoss International Ltd.). The robots were distributed through a new part-work magazine series (Ultimate Real Robots) that had long-term customer usage and retention. A part-work is a serial publication that is issued periodically (e.g., every two weeks), usually in magazine format, and builds into a complete collection. This magazine focused on robotics and was accompanied by cover-mounted component parts that could be assembled, with instructions, by the user to build a working robot over the series. In total, the product contributed over half a million operational domestic robots to the world market, selling over 20 million robot part-work magazines across 18 countries, thereby providing a unique breadth of insight. Gaining a better understanding of the overall attitudes that customers of this product had toward robots in the home, their perception of what such devices could deliver and how they would wish to interact with them should provide results applicable to the domestic appliance, assistance/care, entertainment, and educational markets.

Extended Kalman filtering for robotic proximity sensing

The authors address the problems in using a fiber-optic proximity sensor to detect robot end-effector positioning errors in performing a contact task when uncertainties about target position exist. An extended Kalman filter approach is employed to solve the nonlinear filtering problem. Some experimental results are given.

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.

Modular non-computational-connectionist-hybrid neural network approach to robotic systems

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.