This paper proposes an iterative algorithm to solve the inverse displacement for a hyper-redundant elephant’s trunk robot (HRETR). In this algorithm, each parallel module is regarded as a geometric line segment and point model. According to the forward approximation and inverse pose adjustment principles, the iteration process can be divided into forward and backward iteration. This iterative algorithm transforms the inverse displacement problem of the HRETR into the parallel module’s inverse displacement problem. Considering the mechanical joint constraints, multiple iterations are carried out to ensure that the robot satisfies the required position error. Simulation results show that the algorithm is effective in solving the inverse displacement problem of HRETR.

This paper is concerned with algorithmic techniques for the incremental generation of continuous curves that can efficiently cover an abstract surface. We introduce the notion of low-discrepancy curves as an extension of the notion of low-discrepancy sequences—such that sufficiently smooth curves with low-discrepancy properties can be defined and generated. We then devise a procedure for lifting these curves, that efficiently cover the unit cube, to abstract surfaces, such as nonlinear manifolds. We present algorithms that yield suitable fair mappings between the unit cube and the abstract surface. We demonstrate the application of these ideas using some concrete examples of interest in robotics.

This paper proposes a novel multi-step broadcast control (MBC) scheme to deploy a group of autonomous mobile agents for accomplishing coverage tasks in a bounded region. Traditional broadcast control (BC) schemes use a one-to-all communication framework to transmit a uniform signal to all agents, making it cost-effective compared with any all-to-all communication-based scheme for a multi-agent system. However, as BC schemes are based on a single-step view of the environment for decision-making, the environment’s varying distribution density is not known immediately to the agents, resulting in suboptimal performance. To overcome this drawback, this paper proposes an MBC scheme, where agents use a predictive multi-step view and are able to detect the varying densities in the environment ahead of time. The local controller output is estimated using a weighted averaging technique which assigns a higher weight to immediate steps; this feature compensates for any decrease in prediction accuracy as the number of steps increases. We demonstrate the effectiveness of the proposed MBC scheme using a coverage task over a region with uneven population density. Compared to existing BC schemes, the proposed MBC scheme shows superior convergence characteristics in task accomplishment and deployment efficiency.

Craniovertebral junction (CVJ) is one of the more complex parts of the spinal column. It provides mobility to the cranium and houses the spinal cord. In a healthy subject, the CVJ contributes 25% of the flexion–extension motion and 50% of the axial rotation of the neck. This work reports instrumentation development and results for evaluating implant performance in the stabilized CVJ after surgical procedures. Typically, some bony parts of the vertebrae causing compression to the spinal cord are removed and subsequently stabilized by the instrumenting implant in the CVJ. Pose estimation of the Cadaveric CVJ region is estimated using a monocular vision-based setup. The cervical spine’s first three vertebrae surround the CVJ area, where most cervical spine mobility originates. We aim to evaluate the performance of vision-based intervertebral motion estimation of the Cadaver’s CVJ in the Indian population, particularly in older people. A series of tests were performed on the Cadaver’s CVJ to evaluate the vision system-based motion estimation performance.

In this paper, an overall structure with the asymmetric constrained controller is constructed for human–robot interaction in uncertain environments. The control structure consists of two decoupling loops. In the outer loop, a discrete output feedback adaptive dynamics programing (OPFB ADP) algorithm is proposed to deal with the problems of unknown environment dynamic and unobservable environment position. Besides, a discount factor is added to the discrete OPFB ADP algorithm to improve the convergence speed. In the inner loop, a constrained controller is developed on the basis of asymmetric barrier Lyapunov function, and a neural network method is applied to approximate the dynamic characteristics of the uncertain system model. By utilizing this controller, the robot can track the prescribed trajectory precisely within a security boundary. Simulation and experimental results demonstrate the effectiveness of the proposed controller.

Parallel robots are widely used in the fields of manufacturing, medical science, education, scientific research, etc. Many studies have been conducted on the topic already. However, shortcomings still exist, especially in certain situations. To meet the demand of good speed and load performances at the same time, this work presents a novel 2-degree-of-freedom parallel robot. The structural design, static, stiffness, and reachable workspace analysis of the robot are given in the manuscript. Experiment regarding the accuracy and speed performance is conducted, and the results are provided. In the end, potential applications of the proposed robot are suggested.

This paper presents a novel method for ultrasound speed compensation in ultrasonic robot tracking. It employs optimization algorithms to estimate the best value of the ultrasound speed for every computation of the robot end-effector position. Compared with the other existing method for ultrasound speed compensation, this method has the advantage that no extra equipment is required to monitor the environment conditions (temperature etc.). The simulation, which is described at the end of this paper, shows that the real trajectory is extracted with very good precision from a set of distorted data caused by serious ultrasound speed drifting.

The paper reports on a new multi-view algorithm that combines information from multiple images of a single target object, captured at different distances, to determine the identity of an object. Due to the use of global feature descriptors, the method does not involve image segmentation. The performance of the algorithm has been evaluated on a binary classification problem for a data set consisting of a series of underwater images.

This paper presents a new combined 9-DOF [3R-3R-3R] parallel architecture to perform the object catching in the real-time scenario. The architecture design is intended to carry heavy payload objects for the catching. This paper covers modelling the new architecture, kinematics, and dynamic analyses to compute torques/forces at the actuators. The simulation of kinematic and dynamic analysis in MATLAB. Vision sensors, encoders, PID controller, and current limiting are used to perform object catching. The architecture is the only delta robot application designed to catch regular-shaped objects in real-time scenarios.

In minimally invasive surgery, surgical instruments with a wrist joint have better flexibility. However, the bending motion of the wrist joint causes a coupling motion between the end-effector and wrist joint, affecting the accuracy of the movement of the surgical instrument. Aiming at this problem, a new gear train decoupling method is proposed in the paper, which can automatically compensate for the coupled motion in real-time. Based on the performance tests of the instrument prototype, a series of decoupling effects tests are carried out. The test results show that the surgical instrument has excellent decoupling ability and stable performance.

For a robotic workcell with multiple robots, several interconnection methods are presented in terms of a processor-based architecture. The concept of the multiple processor system (MPS) or multiple computer system (MCS) is used to formulate and analyze the multi-robot interconnection system (MRIS). The MRIS is modelled as a queueing network, and mathematical analysis is done on the basis of modelling. Performance evaluation is achieved for the MRIS through the mean value analysis with the response time and the probability of service failure under different workloads. The results together with some comments suggest a useful guideline for a selecting an appropriate interconnection method for the MRIS subject to the system environment and application.

This paper summarises the results of work carried out in planning the application of a robot in a working cell including a small number of metal cutting machines. The viewpoint assumed is that of a first-time user of robots, and includes the procedure for selecting a robot. Because the analysis calls for robot information not readily available to the user, or which is application specific, a significant conclusion is the necessity to establish a structured programme of collaboration between robot user and robot manufacturer, which becomes an essential part of the analytical and design process.

This report deals with the development of new control vehicles for the bedridden, physically handicapped person who needs a help-system for carrying things to the bedside from the stock in the room. This new control method is characterized by a unit loop system on the drive track. This unit loop system was constructed to execute three actions: stop, backward and right forward movement, under the control of a on-board microcomputer.

This control method is used in small rooms. It also enables one to increase the driving area of a vehicle without reprogramming and adjusting the control mechanism.

A new method for computer forming of dynamic equations of open-chain mechanical robot configurations is presented. The algorithm used is of a numeric-iterative type, based on mathematical apparatus of screw theory, which has enabled elimination of the unnecessary computations in the process of dynamic model derivation. In addition to conventional kinematic schemes of robotic manipulators, the branched kinematic chains which have recently found their application in the locomotion of robotic mechanisms were also treated. Both the inverse and direct problems of dynamics were addressed. A comparative analysis was carried out of the numerical complexity of various existing algorithms of numeric-iterative type dealing with the problems of spatial active mechanisms dynamics. It has been shown that the proposed method regardless of its generality, approaches by its models complexity symbolic models, which are valid for particular robotic mechanisms only where they achieve a high degree of efficiency.

This paper describes the research activities at the Laboratory for Control Systems and Automation (LCA) which is a section of the Production Department of Korea Advanced Institute of Science and Technology (KAIST). LCA's research activities are focused on providing fundamental technologies to cope with the current trends in manufacturing automation. The R & D activities at the laboratory cover diverse areas. The research activities at the laboratory are classified into three sections—robotics and automation, fluid servo control, and manufacturing process control. Detailed explanations are given here on robotics and its application to automation. As a laboratory belonging to a nation's leading educational institution, LCA also conducts active educational activities. Such educational programs are also introduced in detail.