Delays versus performance of visually guided systems

The paper presents an overview of dynamic systems with inherent delays in both feedforward and feedback paths and how the performance of such systems can be affected by such delays. The authors concentrate on visually guided systems, where the behaviour of the system is largely dependent on the results of the vision sensors, with particular reference to active robot heads (real-time gaze control). We show how the performance of such systems can deteriorate substantially with the presence of unknown and/or variable delays. Considered choice of system architecture, however, allows the performance of active vision systems to be optimised with respect to the delays present in the system.

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.

Joint servoing for robust manipulator force control

An experimental and theoretical comparison is made of force control performance with different types of innerloop joint servoing techniques. The problem of disturbance rejection and sensitivity to plant dynamics variations (robustness) is addressed. Position, velocity, strain gauge derived joint torque, and current servos are designed and implemented on a specially instrumented industrial robot, and the end-effector force feedback performances achieved are compared. Joint strain derived torque servoing is found to provide the best overall robust force control performance. Experimental results of the robust hard-on-hard contact achieved with the novel force controller implementation based on joint torque sensing are provided. Conclusions are drawn on the force control performance achievable on a geared robot given the joint servoing technique.

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.

Developing skin analogues for a robotic octopus

In order to fabricate a biomimetic skin for an octopus inspired robot, a new process was developed based on mechanical properties measured from real octopus skin. Various knitted nylon textiles were tested and the one of 10-denier nylon was chosen as reinforcement. A combination of Ecoflex 0030 and 0010 silicone rubbers was used as matrix of the composite to obtain the right stiffness for the skin-analogue system. The open mould fabrication process developed allows air bubble to escape easily and the artificial skin produced was thin and waterproof. Material properties of the biomimetic skin were characterised using static tensile and instrumented scissors cutting tests. The Young’s moduli of the artificial skin are 0.08 MPa and 0.13 MPa in the longitudinal and transverse directions, which are much lower than those of the octopus skin. The strength and fracture toughness of the artificial skin, on the other hand are higher than those of real octopus skins. Conically-shaped skin prototypes to be used to cover the robotic arm unit were manufactured and tested. The biomimetic skin prototype was stiff enough to maintain it conical shape when filled with water. The driving force for elongation was reduced significantly compared with previous prototypes.

Development of biomimetic squid-inspired suckers

Biomechanical properties of squid suckers were studied to provide inspiration for the development of sucker artefacts for a robotic octopus. Mechanical support of the rings found inside squid suckers was studied by bending tests. Tensile tests were carried out to study the maximum possible sucking force produced by squid suckers based on the strength of sucker stalks, normalized by the sucking areas. The squid suckers were also directly tested to obtain sucking forces by a special testing arrangement. Inspired by the squid suckers, three types of sucker artefacts were developed for the arm skin of an octopus inspired robot. The first sucker artefact made of knitted nylon sheet reinforced silicone rubber has the same shape as the squid suckers. Like real squid suckers, this type of artefact also has a stalk that is connected to the arm skin and a ring to give radial support.The second design is a straight cylindrical structure with uniform wall thickness made of silicone rubber. One end of the cylinder is directly connected to the arm skin and the other end is open. The final design of the sucker has a cylindrical base and a concave meniscus top. The meniscus was formed naturally using the surface tension of silicone gel, which leads to a higher level of the liquid around the edge of a container. The wall thickness decreases towards the tip of the sucker opening. Sucking forces of all three types of sucker artefacts were measured. Advantages and isadvantages of each sucker type were discussed. The final design of suckers has been implemented to the arm skin prototypes.

Rhythmic behavior of social insects from single to multibody

Revealing the evolution of well-organized social behavior requires understanding a mechanism by which collective behavior is produced. A well-organized group may be produced by two possible mechanisms, namely, a central control and a distributed control. In the second case, local interactions between interchangeable components function at the bottom of the collective behavior. We focused on a simple behavior of an individual ant and analyzed the interactions between a pair of ants. In an experimental set-up, we placed the workers in a hemisphere without a nest, food, and a queen, and recorded their trajectories. The temporal pattern of velocity of each ant was obtained. From this bottom-up approach, we found the characteristic behavior of a single worker and a pair of workers as follows: (1) Activity of each individual has a rhythmic component. (2) Interactions between a pair of individuals result in two types of coupling, namely the anti-phase and the in-phase coupling. The direct physical contacts between the pair of workers might cause a phase shift of the rhythmic components in individual ants. We also build up a simple model based on the coupled oscillators toward the understanding of the whole colony behavior.

A feasible study of EEG-driven assistive robotic system for stroke rehabilitation

Stroke is a medical emergency and can cause a neurological damage, affecting the motor and sensory systems. Harnessing brain plasticity should make it possible to reconstruct the closed loop between the brain and the body, i.e., association of the generation of the motor command with the somatic sensory feedback might enhance motor recovery. In order to aid reconstruction of this loop with a robotic device it is necessary to assist the paretic side of the body at the right moment to achieve simultaneity between motor command and feedback signal to somatic sensory area in brain. To this end, we propose an integrated EEG-driven assistive robotic system for stroke rehabilitation. Depending on the level of motor recovery, it is important to provide adequate stimulation for upper limb motion. Thus, we propose an assist arm incorporating a Magnetic Levitation Joint that can generate a compliant motion due to its levitation and mechanical redundancy. This paper reports on a feasibility study carried out to verify the validity of the robot sensing and on EEG measurements conducted with healthy volunteers while performing a spontaneous arm flexion/extension movement. A characteristic feature was found in the temporal evolution of EEG signal in the single motion prior to executed motion which can aid in coordinating timing of the robotic arm assistance onset.

Autistic traits modulate mimicry of social but not nonsocial rewards

Autism Spectrum Conditions (ASC) are associated with diminished responsiveness to social stimuli, and especially to social rewards such as smiles. Atypical responsiveness to social rewards, which reinforce socially appropriate behavior in children, can potentially lead to a cascade of deficits in social behavior. Individuals with ASC often show diminished spontaneous mimicry of social stimuli in a natural setting. In the general population, mimicry is modulated both by the reward value and the sociality of the stimulus (i.e., whether the stimulus is perceived to belong to a conspecific or an inanimate object). Since empathy and autistic traits are distributed continuously in the general population, this study aimed to test if and how these traits modulated automatic mimicry of rewarded social and nonsocial stimuli. High and low rewards were associated with human and robot hands using a conditioned learning paradigm. Thirty-six participants from the general population then completed a mimicry task involving performing a prespecified hand movement which was either compatible or incompatible with a hand movement presented to the participant. High autistic traits (measured using the Autism Spectrum Quotient, AQ) predicted lesser mimicry of high-reward than low-reward conditioned human hands, whereas trait empathy showed an opposite pattern of correlations. No such relations were observed for high-reward vs. low-reward conditioned robot hands. These results demonstrate how autistic traits and empathy modulate the effects of reward on mimicry of social compared to nonsocial stimuli. This evidence suggests a potential role for the reward system in underlying the atypical social behavior in individuals with ASC, who constitute the extreme end of the spectrum of autistic traits.

The cyber challenge: a robotics project to enthuse

Robotics is a key theme in many of the degrees offered in Systems Engineering. The topic has proved useful in attracting students to the University, and it also provides the basis of much practical and project work throughout the degrees. This paper focuses on one aspect, a Part 2 project in which students doing various degrees work together to develop a mobile robot which is controlled remotely to navigate an environment and perform specific tasks. In addition to providing practical experience of relevant academic topics, this project helps to contribute to key teaching and learning priorities including problem based learning, motivation and important employability skills.

Estimation of magnet separation for magnetic suspension applications

This thesis describes a form of non-contact measurement using two dimensional hall effect sensing to resolve the location of a moving magnet which is part of a ‘magnetic spring’ type suspension system. This work was inspired by the field of Space Robotics, which currently relies on solid link suspension techniques for rover stability. This thesis details the design, development and testing of a novel magnetic suspension system with a possible application in space and terrestrial based robotics, especially when the robot needs to traverse rough terrain. A number of algorithms were developed, to utilize experimental data from testing, that can approximate the separation between magnets in the suspension module through observation of the magnetic fields. Experimental hardware was also developed to demonstrate how two dimensional hall effect sensor arrays could provide accurate feedback, with respects to the magnetic suspension modules operation, so that future work can include the sensor array in a real-time control system to produce dynamic ride control for space robots. The research performed has proven that two dimensional hall effect sensing with respects to magnetic suspension is accurate, effective and suitable for future testing.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.

Proposal of a floating mechanism based on magnetic levitation method toward EEG-driven robotic system

We discussed a floating mechanism based on quasi-magnetic levitation method that can be attached at the endpoint of a robot arm in order to construct a novel redundant robot arm for producing compliant motions. The floating mechanism can be composed of magnets and a constraint mechanism such that the repelling force of the magnets floats the endpoint part of the mechanism stable for the guided motions. The analytical and experimental results show that the proposed floating mechanism can produce stable floating motions with small inertia and viscosity. The results also show that the proposed mechanism can detect small force applied to the endpoint part because the friction force of the mechanism is very small.