As the proportion of the elderly population in the USA expands, so will the demand for rehabilitation and social care, which play an important role in maintaining function and mediating motor and cognitive decline in older adults. The use of social robotics and telemedicine are each potential solutions but each have limitations. To address challenges with classical telemedicine for rehabilitation, we propose to use a social robot-augmented telepresence (SRAT), Flo, which was deployed for long-term use in a community-based rehabilitation facility catering to older adults. Our goals were to explore how clinicians and patients would use and respond to the robot during rehab interactions. In this pilot study, three clinicians were recruited and asked to rate usability after receiving training for operating the robot and two of them conducted multiple rehab interactions with their patients using the robot (eleven patients with cognitive impairment and/or motor impairment and 23 rehab sessions delivered via SRAT in total). We report on the experience of both therapists and patients after the interactions.

There is an unavoidable time offset between the camera stream and the inertial measurement unit (IMU) data due to the sensor triggering and transmission delays, which will seriously affect the accuracy of visual-inertial odometry (VIO). A novel online time calibration framework via double-stage EKF for VIO is proposed in this paper. First, the first-stage complementary Kalman filter is constructed by adapting the complementary characteristics between the accelerometer and the gyroscope in the IMU, where the rotation result predicted by the gyroscope is corrected through the measurement of the accelerometer so that the IMU can output a more accurate initial pose. Second, the unknown time offset is added to the state vector of the VIO system. The estimated pose of IMU is used as the prediction information, and the reprojection error of multiple cameras on the same feature point is used as the constraint information. During the operation of the VIO system, the time offset is continuously calculated and superimposed on the IMU timestamp to obtain the data synchronized by the IMU and the camera. The Schur complement model is used to marginalize the camera state that carries less information in the system state, avoiding the loss of prior information between images, and improving the accuracy of camera pose estimation. Finally, the effectiveness of proposed algorithm is verified using the EuRoC dataset and the real experimental data.

ADVANCES IN ROBOTIC TECHNIQUES

1. Robotics in Medicine

There have been a number of reports in this section of the progress being made in applying robotic techniques to medical processes. High on the list of achievements in this area have been the attempts to help in surgical operations. Already reports here have dealt with improved aids for surgeons with increased facilities for viewing and of producing images of the patient's progress. Indeed, operations assisted by links with remote centres of expertise and with internet information databanks are no longer unusual. All of these facilities and devices have been, in the main, aids to the operating medical staff but automated surgery still remains a remote goal, although there are many experimental systems in existence. From the Pennsylvania Hershey Medical Centre, USA, however, comes a report of a truly robotic heart surgeon called Zeus. On this occasion it appears that Zeus is not some robotics researchers speculative design for an automated medical robot but a working system that is starting its medical trials in a real-life hospital.

People search can be reformulated as submodular maximization problems to achieve solutions with theoretical guarantees. However, the number of submodular function outcome is $2^N$ from N sets. Compressing functions via nonlinear Fourier transform and spraying out sets are two ways to overcome this issue. This research proposed the submodular deep compressed sensing of convolutional sparse coding (SDCS-CSC) and applied the Topological Fourier Sparse Set (TFSS) algorithms to solve people search problems. The TFSS is based on topological and compressed sensing techniques, while the CSC is based on DCS techniques. Both algorithms enable an unmanned aerial vehicle to search for the people in environments. Experiments demonstrate that the algorithms can search for the people more efficiently than the benchmark approaches. This research also suggests how to select CSC or TFSS algorithms for different search problems.

A flexible apple sorting hand-claw with three fingers evenly on the spiral chuck is designed. Each finger with series double hinges is driven by one air-cylinder. Sizes of hand-claw and parameters of two torsion springs round axes of series double hinges are obtained via global optimization based on the grid method so that the two torsion springs exhibit a coordinative function to enhance compliance for grasping apples of different sizes under the same system pressure. Besides, the critical pressures and bending deflection between different working processes are studied. Results show that hinge 2 begins to rotate at 0.0270 MPa pressure, and when the pressure increases to 0.0634 MPa and 0.0746 MPa, hand-claw begins to touch the biggest and the smallest apples respectively. The curve of torsional angle versus pressure presents that angular velocity droops with homogeneous extension. Therefore, it is able to reduce impact and time in vain during the grasping process. Crucially, the grasping forces for grasping the smallest and the biggest apple are 4 N and 4.38 N respectively under the same 0.5 MPa pressure, indicating the excellent adaption performance and robust result for size variation of apples without any force sensors.

An advanced sonar morphology-based posterior approach (SMP) to building an occupancy grid map for a mobile robot is proposed in this study. It is very important for a mobile robot to find its surrounding saliencies and to localize itself for indoor navigation. Ultrasonic sensors are of great practical value in building environmental maps and for autonomous operation. However, grid maps constructed by ultrasonic sensors cannot typically form a realistic representation of a given environment due to incorrect sonar measurements caused by specular reflection and wide beam width. The sonar sensor model proposed in this study, in which the negative effect of incorrect sonar measurements is minimized by geometric association with sonar footprints, is adopted to build a high-quality grid map. Experimental results and evaluations in home and corridor environments demonstrate the validity of the proposed methods.

Despite the numerous technical improvements, robot programming is still today a very tedious activity requiring considerable efforts for fine tuning programs written off-line. Moreover, such programs are usually not particularly portable from one robot to another, sometimes even when the robots are from the same maker.

The issue addressed in the work reported here is how to overcome these shortcomings. In this respect, the argument is to develop programs within the behaviour-based assembly paradigm which views tasks in terms of goal-achieving entities (behaviours). The focus on the description of a task more than its implementation is the key to generality and portability. As shown with the aid of two similar, but not identical, assembly benchmarks, behavioural programs are independent of any specificity of each assembly kit and can, indeed, be constructed using the very same code.

Patients with damage to the cerebellum make reaching movements that are uncoordinated or “ataxic.” One prevailing hypothesis is that the cerebellum functions as an internal model for planning movements, and that damage to the cerebellum results in movements that do not properly account for arm dynamics. An exoskeleton robot was used to record multi-joint reaching movements. Subsequently, joint-torque trajectories were calculated and a gradient descent algorithm found optimal, patient-specific perturbations to actual limb dynamics predicted to reduce directional reaching errors by an average of 41%, elucidating a promising form of robotic intervention and adding support to the internal model hypothesis.

A robotic manipulator’s classical mechanical capabilities are governed by the design parameters (mass, geometry, dimensions, etc.) of its kinematic pairs and its architecture (number of limbs, degrees of freedom, actuation ability, etc.). Using Clifford-Algebraic and network theoretic methods, this work presents a novel-theoretical framework which allows any two robot architectures and design parameters to be mathematically related to one another through combinations of discrete operators or ‘reassembling transformations’. Two theoretical case studies involving a 6R manipulator and Klann linkage are furnished in this work.

This paper concerns with comparing simulation studies for a newly developed concept of turning point to be used in multiple robot path planning. Different critical factors and design parameters are collected and statistical analyses are performed. After configuring different simulation scenarios, the efficient one is evaluated using a robust data envelopment analysis (RDEA). Due to uncertain aspects of various simulations scenarios, robust version of data envelopment analysis is proposed. Here, major criteria in robot path planning are deadlock and conflict avoidance, throughput, mean flow time, and effective total distance travelled. To determine the effective experiment for the proposed simulation model, RDEA is used. A comparative study with respect to different experiments having various simulation setting is developed. The results for a real robotic manufacturing cell system show effectiveness of the proposed process. Also, the efficient simulation software is determined by multiaspect analysis.

This paper introduces a new approach to robust path planning for mobile robots entirely based on information from environment perception sensors. This method avoids the use of odometry which leads to the accumulation of errors resulting from the robot's position computing. We proceed as follows: we create regions inside which the robot detects the same obstacle segments. A node graph represents all the regions and their links. Then a planning algorithm is used to find a path which joins a start to a goal region. The final stage consists in applying a robust robot motion control as regards the uncertainties of the environment model. This approach contributes to a control system for indoor robots which is environment referenced. The sensors we deal with are first a continuous laser or ultrasonic scanning system, then a discrete ultrasonic belt whose limits of use we show.

Underwater vehicles are rich systems with attractive and challenging properties such as nonlinearities, external disturbances, and underactuated dynamics. These make the design of an advanced and robust controller quite a challenging task. This paper focuses on designing a model-free high-order sliding mode controller in a six-degree-of-freedom trajectory tracking task. The purpose of the control is accurate trajectory tracking and considerably reducing the chattering phenomenon in situations where the remotely operated vehicle (ROV) works in the presence of external disturbances, measurement errors, and actuator dynamics and nonlinearity, which is not seen in previous research. To demonstrate the stability of the closed-loop system, the Lyapunov theory is employed to ensure the asymptotic stability of tracking errors. A linear Kalman filter for estimating measurement errors is proposed to be used to correct positioning system outputs (speed, position, and attitude). In a hardware-in-the-loop test, the proposed controller for the ROV is tested in a real-time application, considering external disturbances, measurement errors, and actual thrusters. In addition, comparing the outcomes with the performance of the PID controller and the supper twisting controller shows the superiority of the proposed controller. Due to the existence of the measurement noise, spectrum analysis is also performed.

It is an established fact that a majority of a product's cost is determined by its design. Hence, effort should be directed to achieve a lower cost design without sacrificing the original functionality. A computer-aided product redesign system is proposed to provide help in generating assembly-oriented redesign by taking the robotic assembly constraints into consideration. The system operates in two phases: In the first phase, an objective evaluation of the input design is performed to determine whether there is a need for redesign. During the second phase, the focus is to aid the designer in searching for feasible design alternatives. Three quantitative measures have been proposed to evaluate the conformity of an input design to a list of DFA design guidelines. If the input design received a bad evaluation results on any of the three measures, a search for feasible redesign suggestions is initiated to derive suitable redesign suggestions.

This paper focuses on the design, analysis, and multi-objective optimization of a novel 5-degrees of freedom (DOF) double-driven parallel mechanism. A novel 5-DOF parallel mechanism with two double-driven branch chains is proposed, which can serve as a machine tool. By installing two actuators on one branch chain, the proposed parallel mechanism can achieve 5-DOF of the moving platform with only three branch chains. Afterwards, analytical solution for inverse kinematics is derived. The 5$\times$5 homogeneous Jacobian matrix is obtained by transforming actuator velocities into linear velocities at three points on the moving platform. Meanwhile, the workspace, dexterity, and volume are analyzed based on the kinematic model. Ultimately, a stage-by-stage Pareto optimization method is proposed to solve the multi-objective optimization problem of this parallel mechanism. The optimization results show that the workspace, compactness, and dexterity of this mechanism can be improved efficiently.

In this paper, we propose a two-loop structure to transform and stabilize the kinematic model of a nonholonomic mobile robot with two independently driven wheels. This two-loop structure consists of input-output pseudolinearization and gain scheduling techniques. A comparison with previous methods is included. The main contribution of this paper is to apply a input-output pseudolinearization transformation method and to use an effective pole-assignment strategy for stabilizing a mobile robot with two independently driven wheels. The proposed method has demonstrated superiority over previous methods.

Bending and elongation have been some of the most studied motions in soft actuators due to the variety of their applications. For that matter, multi-DOF actuators have been developed with the purpose to generate different movements in a single actuator, mainly bending.

However, these actuators are still limited in mobility range, and some of them do not perform continuous curvatures. This paper presents the design, characterisation and implementations of a multi-DOF soft pneumatic module. The internal structure of the proposed module is composed of four channels, which generate bending in several directions. The finite element method analysis demonstrates that the actuator performs continuous curvatures for different pressure values. We present a repeatable and easy manufacturing process using the casting technique, considering the material Ecoflex 00-50; as well as the kinematic model of the actuator, taking into consideration two bending Degrees of Freedom (DOFs). Furthermore, we performed bending characterisation for all possible combinations of the four channels via computer vision, demonstrating a wide mobility range and performing continuous curvatures. Additionally, we evaluated the kinematic model with characterisation data, obtaining the angular and cartesian relationship between the pressure and continuous curvatures. On the other hand, the authors propose the design of a modular soft manipulator based on two multi-DOF modules. The kinematic model is reported. In addition, we implement a motion sequence in the manipulator to pick and place tasks.

Due to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on vector-format fuzzy variables. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environ-ment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.

Dexterity and workspace are two of the most important design criteria in developing manipulators. This paper presents algorithms for developing contour surfaces with specified dexterities and evaluating the area of the surfaces or the volume of the enclosed regions. The obtained results can be utilized to evaluate the dexterity and the rate of change of dexterity. Any closed curve or surface can be used to determine the singularity-free workspace of a manipulator with better dexterity. The proposed algorithms can be employed to study the dexterity and singularity-free workspace of 3-DOF manipulators and 4-DOF redundant serial manipulators. The contour surfaces in some subspaces of 6-DOF manipulators can also be investigated.