With the progress of industry, people are facing more and more complicated tasks, which cannot be completed by conventional rigid robot. For this, a deployable robot based on spherical linkage parallel mechanism was proposed to satisfy relevant requirements for the degrees of freedom in this study. Based on the design of robot model and its control box, a mathematical model for the robot was established, and the relationship between motion space and drive space was deduced accordingly. Subsequently, a control system consisting of the upper and lower computers was introduced. Two control modes, that is, Joystick control and remote control, were developed. The upper computer control interface for the robot was completed by MATLAB construction. At last, the two control modes as well as autonomous detection were demonstrated by motion test. This achievement will further advance the applications of deployable robot in job aid and intelligent exploration.

A laser range finder mounted on a site and azimuth turret is used as a 3D range camera. It forms, associated with a video camera, an original stereovision system. The internal structure of both images are the same but the resolution of 3D image stays low. By ignoring the acquiring speed of measures, spatial resolution is limited by the accuracy of deviation device and the laser footprint. The fact that the impact of the beam is not a point introduces spatial integration.

To correct the average at depth discontinuities due to the beam footprint, a neural-network-based solution is reported.

The use of such a multisensor system requires its calibration. As camera calibration is a well-known problem, the paper focuses on models and calibration methods of the range finder. Experimental results illustrate the quality of the calibration step in terms of accuracy and stability.

The footprint correction is evaluated for both 1D and 2D range finder scannings.

This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach.

In the paper, a new adaptive control law for controlling robot manipulators is derived based on the Lyapunov theory; trigonometric functions are used for the derivation of the parameter estimation law. In this note, we have derived a logarithmic parameter estimation law based on a previous paper, and the boundedness of tracking error has been shown.

The paper deals with the modelling of unknown objects and location determination of known ones. The operator models objects using data issued from the video image and a time of flight infra red range finder. We present methods to build an embodying volume for unknown objects. These methods are available for polyhedral and conical objects, which represent the basis of most industrial environments. The location determination of known objects is determined using 2D clues obtained through video image. A two-step algorithm is implemented and assessed. The first step is available in case of object large motion, it is a geometric algorithm, which doesn't use redundant data; it provides a first estimate of the pose. The second step is available in case of object small motion. A linear approach is carried out to determine the pose. It allows the use of redundant data, so it improves the accuracy achieved after the first step.

The four papers encompassing this special section on Robot Mediated Neuro-motor Therapy introduce a new area for robotics in the healthcare industry, that of assisting in the delivery of neuro-motor therapies, for patients recovering from a stroke. As life expectancy increases, so do problems associated with old age. In the paper by Krebs et al. the authors not only summarise the need for action in stroke rehabilitation but also makes a useful distinction between assistive technologies that provide enhanced abilities for the patient, and therapy tools for the clinician, that seek to enhance the patients recovery.

Engineers have traditionally invested in Advanced Manufacturing Technology (AMT), such as FMS, Robots, CAD/CAM, CNC and MRP to achieve a reduction in the labour force. Similarly, government incentives for introducing AMT, have also placed an undue emphasis on the ‘need to replace labour with technology’. This policy creates severe industrial relations problems and leads to the view that technology, especially robots, ‘competes’ with human beings for employment. Research at U.M.I.S.T. has shown that AMT is much more viable when the objective of the investment is to increase a company's overall competitive ability, thereby generating increased sales which, in turn, necessitates an INCREASED labour force. The paper discusses various aspects of AMT and in each case it is shown how the acceptability of the investment is improved when the new technology is viewed ‘company-wide’. When this occurs, technology is viewed as being ‘complementary to’ and not ‘instead of’ humans.

This paper presents a new method for solving the inverse kinematics of robot manipulators. The method defines incremental units in joint and Cartesian spaces, which represent the position resolutions in each space. Based on these units, the incremental computation of the DDA integrator is used to solve the direct kinematics. The repetitive calculation of the inverse Jacobian matrix is replaced by a simple look-up table. By using an iterative procedure with convergence rules, the inverse kinematics algorithm is established. A 3 DOF robot is considered as the combination of two types of a 2 DOF robot. Simulation and experiment are performed to test the algorithm.

This paper proposes an approach for the high-level programming of co-designed robots that reduces programming complexity. Particularly, the work presented focuses on the programming framework of an intelligent system, based on the IEEE Standard Ontologies for Robotics and Automation, which allows users the automatic design of robots and the automatic implementation of controllers in the Robot Operating System (ROS). In our approach, the co-designed robot functionalities are automatically translated into visual programming blocks allowing non-expert users an easy robot programming by means of a visual programming language. Several robot configurations and three case studies are provided as a proof of concept. The validation, in terms of usability, of the framework has been carried out with inexperienced users showing promising results.

Multi-legged robots with rigid-flexible coupling grippers have appealing applications to asteroid exploration with the microgravity. However, these robots usually have significantly complicated structures, which leads to a great challenge for the kinematic design.This paper proposes the kinematic design method for a novel multi-legged robot with the microspine gripper. First, the structure of the multi-legged asteroid exploration robot and the microspine gripper are demonstrated. Second, four performance evaluation indices, which are used to evaluate the stiffness, velocity, motion / force transfer efficiency and gripper attachment efficiency of the robot, are derived from the kinematic model. Non-dimensional design spaces of parameters to be optimized are drawn, and performance atlases are presented in design spaces. Third, the stiffness model of the microspine is derived. In addition, the constraint condition of the restoring spring is established, and the stiffness of restoring springs are optimized using the genetic algorithm. Several experiments are conducted to verify the stiffness model of the microspine. Finally, the prototype is developed and the experimental results validates the kinematic design method.

The objective of this work is to construct a robot that is based on 3D printing to meet the low-cost and light structures. The Computer-aided-design model is used with LabVIEW to simulate the given trajectory. Users of the simulation of such methodology can preview the simulated motion and perceive and resolve discrepancies between the planned and simulated paths prior to execution of a task. The advantages of this study are the lack of need to mount extra sensors on realistic robot to measure joint space coordinates, simplifying the hardware. These outcomes can also be used in an undergraduate robotics course.

There is an increasing popularity of mobile robot applications over the Internet. Robots need some kind of wireless communication to receive commands and transmit information to users. This paper describes the problems encountered to keep the mobile robots connected and the solutions adopted. The first problem was related to delays and the very low throughput that occur when the robot roams to a new access point. Most commercial systems currently installed implement proprietary solutions with different behaviors. Here, a simple and device-independent solution for mobile robot applications is proposed. The second problem is the lack of wireless coverage in some areas of buildings. The solutions adopted for these problems are based on coverage maps.

It is very challenging for robots to perform grinding and polishing tasks on surfaces with unknown geometry. Most existing methods solve this problem by modeling the relationship between the force sensing information and surface normal vectors by analyzing the forces on special end tools such as spherical tools and cylindrical tools and simplified friction model. In this paper, we propose a normal vectors learning method to simultaneously control end-effector force and direction on unknown surfaces. First, the relation that mapping the force sensing information to the surface normal vectors is learned from the demonstrated data on the known plane using locally weighted regression. Next, the learned relation is used to estimate surface normal vectors on the unknown surface. To improve the force control precision on the unknown geometry surface, the adaptive force control is developed. To improve the direction control precision due to friction, the iterative learning control is developed. The proposed method is verified by comparative simulations and experiments using the Franka robot. Results show that the end-effector can be controlled perpendicular to the surface with a certain force.

Navigating along a set of programmed points in a completely unknown environment is a challenging task which mostly depends on the way the robot perceives and symbolizes the environment and decisions it takes in order to avoid the obstacles while it intends to reach subsequent goals. Tenacity and Traversability (T2)1-based strategies have demonstrated to be highly effective for reactive navigation, extending the benefits of the artificial Potential Field method to complex situations, such as trapping zones or mazes. This paper presents a new approach for reactive mobile robot behavior control which rules the actions to be performed to avoid unexpected obstacles while the robot executes a mission between several defined sites. This new strategy combines the T2 principles to escape from trapping zones together with additional criteria based on the Nearness Diagram (ND)13 strategy to move in cluttered or densely occupied scenarios. Success in a complete set of experiments, using a mobile robot equipped with a single camera, shows extensive environmental conditions where the strategy can be applied.

We proposed a compliant leg configuration that enhances the conventional pantograph design with leaf springs. The following facts characterize the proposed configuration: (1) Due to the use of the pantograph structure, the mass is centralized around the hip joint, reducing the lower leg inertia; (2) Leaf springs are chosen as elastic parts to increase energy efficiency and estimate foot-end contact forces. Compared with coil springs, leaf springs require no guide rails to deploy, and their stiffness can be easily adjusted through shape cutting. Analytical models are introduced to analyze the leg’s stiffness and estimate the contact forces only with the deflections of leaf springs. A one-leg robot based on the proposed design is built, and various experiments are conducted. Experiments regarding the stiffness calibration and the contact forces estimation showed an acceptable agreement with the analytical model. Experiments of dropping demonstrate the feasibility of the leg to perform spring-like behaviors. Experiments of periodic hopping demonstrate the feasibility of using spring deflections to detect touch-down events. For energy efficiency, it is also observed that the elastic leg has a 20% increment concerning the jumping height in the flight phase, compared with the one where leaf springs are replaced with rigid materials.