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In order to bridge the increasing gap between the micro‐ and nanotechnologies, a European consortium is currently developing and investigating a cluster of mobile, wireless cubic centimetre‐sized microrobots. The control and sensor issues which are to be solved for such a robot system are demanding. This paper describes the work carried out by one of the project partners. An interferometrical principle employing the so‐called “mechanical” interferometer based on the Moiré‐effect is used for the position sensor system. Further sensor systems involve “local” microscope cameras, for which the extraction of depth information is crucial.

Tactile sensing is the process of determining physical properties and events through contact with objects in the world. The purpose of this paper is to establish a novel design of an adaptive neuro-fuzzy inference system (ANFIS) for estimation of contact position of a new tactile sensing structure.

The major task is to investigate implementations of carbon-black-filled silicone rubber for tactile sensation; the silicone rubber is electrically conductive and its resistance changes by loading or unloading strains.

The sensor-elements for the tactile sensing structure were made by press-curing from carbon-black-filled silicone rubber. The experimental results can be used as training and checking data for the ANFIS network.

This system is capable to find any change of contact positions and thus indicates state of the current contact location of the tactile sensing structure. The behavior of the use silicone rubber shows strong non-linearity, therefore, the sensor cannot be used for high accurate measurements. The greatest advantage of this sensing material lies in its high elasticity.

With enhanced use of humanoids in demanding sectors of industrial automation and smart manufacturing, navigation and path planning of humanoid forms have become the centre of attraction for robotics practitioners. This paper aims to focus on the development and implementation of a hybrid intelligent methodology to generate an optimal path for humanoid robots using regression analysis, adaptive particle swarm optimization and adaptive ant colony optimization techniques.

Sensory information regarding obstacle distances are fed to the regression controller, and an interim turning angle is obtained as the initial output. Adaptive particle swarm optimization technique is used to tune the governing parameter of adaptive ant colony optimization technique. The final output is generated by using the initial output of regression controller and tuned parameter from adaptive particle swarm optimization as inputs to the adaptive ant colony optimization technique along with other regular inputs. The final turning angle calculated from the hybrid controller is subsequently used by the humanoids to negotiate with obstacles present in the environment.

As the current investigation deals with the navigational analysis of single as well as multiple humanoids, a Petri-Net model has been combined with the proposed hybrid controller to avoid inter-collision that may happen in navigation of multiple humanoids. The hybridized controller is tested in simulation and experimental platforms with comparison of navigational parameters. The results obtained from both the platforms are found to be in coherence with each other. Finally, an assessment of the current technique with other existing navigational model reveals a performance improvement.

The proposed hybrid controller provides satisfactory results for navigational analysis of single as well as multiple humanoids. However, the developed hybrid scheme can also be attempted with use of other smart algorithms.

Humanoid navigation is the present talk of the town, as its use is widespread to multiple sectors such as industrial automation, medical assistance, manufacturing sectors and entertainment. It can also be used in space and defence applications.

This approach towards path planning can be very much helpful for navigating multiple forms of humanoids to assist in daily life needs of older adults and can also be a friendly tool for children.

Humanoid navigation has always been tricky and challenging. In the current work, a novel hybrid methodology of navigational analysis has been proposed for single and multiple humanoid robots, which is rarely reported in the existing literature. The developed navigational plan is verified through testing in simulation and experimental platforms. The results obtained from both the platforms are assessed against each other in terms of selected navigational parameters with observation of minimal error limits and close agreement. Finally, the proposed hybrid scheme is also evaluated against other existing navigational models, and significant performance improvements have been observed.

The aim of this paper is to investigate implementations of carbon‐black filled silicone rubber for tactile sensation.

The sensor‐elements for this tactile sensing structure were made by press‐curing from carbon‐black filled silicone rubber.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor cannot be used for accurate measurements. The greatest advantage of this material lies in its high elasticity.

A new method for artificial tactile sensing skin for robotic applications.

The purpose of this paper is to investigate the effect of time delay on the ability of a human operator to complete a task with a teleoperated mobile‐robot using two systems, two different ways of interacting with the mobile‐robots and several different environments.

Teleoperators are observed completing a series of tasks using a joystick to control a mobile‐robot while time delays are introduced to the system. They sit at a computer and view scenes remotely on a screen. Cameras are either mounted on the robot or mounted externally so that they view both the environment and robot. Teleoperators complete the tests both with and without sensors. One robot system uses an umbilical cable and one uses a radio link.

In simple environments, a teleoperator may perform better without a sensor system to assist them but as time delays are introduced then there are more failures. In more complicated environments or when time delays are longer, then teleoperators perform better with a sensor system to assist. Teleoperators may also tend to perform better with a radio link than with an umbilical connection.

Teleoperated systems rely heavily on visual feedback and experienced operators. This paper investigates the effect of introducing a delay to the delivery of that visual feedback.

The paper suggests that in simple environments with short time delays then the amount of sensor support should be small but in more complicated environments or with longer delays then more sensor support needs to be provided.

Results from imposing time delays on a teleoperated mobile‐robot are presented. Effects on the task of different ways of viewing activity on a computer display are presented, that is with cameras mounted on the robot or cameras mounted externally to view both the environment and robot. Results from using sensors to assist teleoperators are presented. The paper suggests that the amount of sensor support should be varied depending on circumstances.

Industrial robots are extensively deployed to perform repetitive and simple tasks at high speed to reduce production time and improve productivity. In most cases, a compliant gripper is used for assembly tasks such as peg-in-hole assembly. A compliant mechanism in the gripper introduces flexibility that may cause oscillation in the grasped object. Such a flexible gripper–object system can be considered as an under-actuated object held by the gripper and the oscillations can be attributed to transient disturbance of the robot itself. The commercially available robots do not have a control mechanism to reduce such induced vibration. Thus, this paper aims to propose a contactless vision-based approach for vibration suppression which uses a predictive vibrational amplitude error-based second-stage controller.

The proposed predictive vibrational amplitude error-based second-stage controller is a real-time vibration control strategy that uses predicted error to estimate the second-stage controller output. Based on controller output, input trajectories were estimated for the internal controller of the robot. The control strategy efficiently handles the system delay to execute the control input trajectories when the oscillating object is at an extreme position.

The present controller works along with the internal controller of the robot without any interruption to suppress the residual vibration of the object. To demonstrate the robustness of the proposed controller, experimental implementation on Asea Brown Boveri make industrial robot (IRB) 1410 robot with a low frame rate camera has been carried out. In this experiment, two objects have been considered that have a low (<2.38 Hz) and high (>2.38 Hz) natural frequency. The proposed controller can suppress 95% of vibration amplitude in less than 3 s and reduce the stability time by 90% for a peg-in-hole assembly task.

The present vibration control strategy uses a camera with a low frame rate (25 fps) and the delays are handled intelligently to favour suppression of high-frequency vibration. The mathematical model and the second-stage controller implemented suppress vibration without modifying the robot dynamical model and the internal controller.

Industrial robots are extensively used in the robotic assembly of rigid objects, whereas the assembly of flexible objects using the same robot becomes cumbersome and challenging due to transient disturbance. The transient disturbance causes vibration in the flexible object during robotic manipulation and assembly. This is an important problem as the quick suppression of undesired vibrations reduces the cycle time and increases the efficiency of the assembly process. Thus, this study aims to propose a contactless robot vision-based real-time active vibration suppression approach to handle such a scenario.

A robot-assisted camera calibration method is developed to determine the extrinsic camera parameters with respect to the robot position. Thereafter, an innovative robot vision method is proposed to identify a flexible beam grasped by the robot gripper using a virtual marker and obtain the dimension, tip deflection as well as velocity of the same. To model the dynamic behaviour of the flexible beam, finite element method (FEM) is used. The measured dimensions, tip deflection and velocity of a flexible beam are fed to the FEM model to predict the maximum deflection. The difference between the maximum deflection and static deflection of the beam is used to compute the maximum error. Subsequently, the maximum error is used in the proposed predictive maximum error-based second-stage controller to send the control signal for vibration suppression. The control signal in form of trajectory is communicated to the industrial robot controller that accommodates various types of delays present in the system.

The effectiveness and robustness of the proposed controller have been validated using simulation and experimental implementation on an Asea Brown Boveri make IRB 1410 industrial robot with a standard low frame rate camera sensor. In this experiment, two metallic flexible beams of different dimensions with the same material properties have been considered. The robot vision method measures the dimension within an acceptable error limit i.e. ±3%. The controller can suppress vibration amplitude up to approximately 97% in an average time of 4.2 s and reduces the stability time up to approximately 93% while comparing with control and without control suppression time. The vibration suppression performance is also compared with the results of classical control method and some recent results available in literature.

The important contributions of the current work are the following: an innovative robot-assisted camera calibration method is proposed to determine the extrinsic camera parameters that eliminate the need for any reference such as a checkerboard, robotic assembly, vibration suppression, second-stage controller, camera calibration, flexible beam and robot vision; an approach for robot vision method is developed to identify the object using a virtual marker and measure its dimension grasped by the robot gripper accommodating perspective view; the developed robot vision-based controller works along with FEM model of the flexible beam to predict the tip position and helps in handling different dimensions and material types; an approach has been proposed to handle different types of delays that are part of implementation for effective suppression of vibration; proposed method uses a low frame rate and low-cost camera for the second-stage controller and the controller does not interfere with the internal controller of the industrial robot.

The purpose of this paper is to present powered‐wheelchair transducers and systems that provide more control, reduced veer on slopes, and improved energy conservation, while reducing effort. They are especially significant for people with movement disorders who lack sufficient hand‐grasp and release ability or sufficient targeting skill to use joysticks.

Laboratory test rigs are created to test proportional switches and teach potential users. Then, trials are conducted with a rolling road and in real situations. Caster angle‐measurement is selected to provide feedback to minimize drift away from a chosen course and an electronic solution was created to match driver control to caster‐steering‐position. A case study is described as an example.

Results and advantages are presented from changing from using a set of digital‐switches to a set of new variable‐switches and then adding a sensor system to prevent veer on slopes. Systems have been tested for nearly two years and shown to assist powered‐wheelchair‐users with poor targeting skills.

The research used wheelchairs with caster‐wheels but the systems could easily be used on other wheelchairs.

Simple input‐devices are presented that isolate gross motor function and are tolerant to involuntary movements (proportional‐switches). A sensor system is presented that assists users in steering across sloping or uneven ground.

Proportional‐switches and sensors are shown to reduce veer and provide more control over turn and forward speed and turn radius while reducing frustration and improving energy conservation. The simple and affordable systems could be created and attached to many standard powered‐wheelchairs in many organisations.

The purpose of this paper is to investigate the effect on time to complete a task depending on how a human operator interacts with a mobile‐robot. Interaction is investigated using two tele‐operated mobile‐robot systems, three different ways of interacting with robots and several different environments. The speed of a tele‐operator in completing progressively more complicated driving tasks is investigated also.

Tele‐operators are timed completing a series of tasks using a joystick to control a mobile‐robot. They either watch the robot while operating it, or sit at a computer and view scenes remotely on a screen. Cameras are either mounted on the robot, or so that they view both the environment and robot. Tele‐operators complete tests both with and without sensors. One robot system uses an umbilical cable and one uses a radio link.

In simple environments, a tele‐operator may perform better without a sensor system to assist them but in more complicated environments then a tele‐operator may perform better with a sensor system to assist. Tele‐operators may also tend to perform better with a radio link than with an umbilical connection. Tele‐operators sometimes perform better with a camera mounted on the robot compared with pre‐mounted cameras observing the environment (but that depends on tasks being performed).

Tele‐operated systems rely heavily on visual feedback and experienced operators. This paper investigates how to make tasks easier.

The paper suggests that the amount of sensor support should be varied depending on circumstances.

Results show that human tele‐operators perform better without the assistance of a sensor systems in simple environments.

The purpose of this paper is to investigate the effect on completion of mobile‐robot tasks depending on how a human tele‐operator interacts with a sensor system and a mobile‐robot.

Interaction is investigated using two mobile‐robot systems, three different ways of interacting with the robots and several different environments of increasing complexity. In each case, the operation is investigated with and without sensor systems to assist an operator to move a robot through narrower and narrower gaps and in completing progressively more complicated driving tasks. Tele‐operators used a joystick and either watched the robot while operating it, or sat at a computer and viewed scenes remotely on a screen. Cameras are either mounted on the robot to view the space ahead of the robot or mounted remotely so that they viewed both the environment and robot. Every test is compared with sensor systems engaged and with them disconnected.

A main conclusion is that human tele‐operators perform better without the assistance of sensor systems in simple environments and in those cases it may be better to switch‐off the sensor systems or reduce their effect. In addition, tele‐operators sometimes performed better with a camera mounted on the robot compared with pre‐mounted cameras observing the environment (but that depended on tasks being performed).

Tele‐operators completed tests both with and without sensors. One robot system used an umbilical cable and one used a radio link.

The paper quantifies the difference between tele‐operation control and sensor‐assisted control when a robot passes through narrow passages. This could be an useful information when system designers decide if a system should be tele‐operated, automatic or sensor‐assisted. The paper suggests that in simple environments then the amount of sensor support should be small but in more complicated environments then more sensor support needs to be provided.

The paper investigates the effect of completing mobile‐robot tasks depending on whether a human tele‐operator uses a sensor system or not and how they interact with the sensor system and the mobile‐robot. The paper presents the results from investigations using two mobile‐robot systems, three different ways of interacting with the robots and several different environments of increasing complexity. The change in the ability of a human operator to complete progressively more complicated driving tasks with and without a sensor system is presented and the human tele‐operators performed better without the assistance of sensor systems in simple environments.