A novel hybrid robotic arm with three fingers is proposed for assembly, operation and rescue. It is composed of an upper 3RPS-type parallel manipulator, a lower 3SPR-type parallel manipulator and three fingers. Its dynamics are studied and analyzed systematically. First, the kinematics formulae of the moving links at their mass centers in the hybrid robotic arm with three fingers are established. Second, the formulae for solving the inertial wrench of the moving links at their mass centers are derived. Third, a dynamics formula is established for solving the dynamic active/constrained forces of the hybrid robotic arm and the fingers. Finally, an analytic example is given for solving the kinematics and dynamics of the hybrid robotic arm with three fingers and the analytic solved solutions are verified by a simulation mechanism.

This paper presents a methodology for image-to-space path planning of a SCARA manipulator with a single static color camera. The method proposes a two step algorithm for estimating object position on the image plane and then mapping into space to find required angular values of the manipulator joints. Tests were carried with a computational routine to estimate position on the image plane of a set of different fruits under natural light conditions. Finally the method was tested using a robotic arm and similarly structured objects. Hardware and software implementation of the present method is of low cost when compared to current commercial technology, and operational results are promising but dependent on environmental illumination control and camera calibration accuracy. The methodology is intended to be applied in the automatic classification of fruits.

An observation approach is proposed for determining the poses of the active/constrained wrench and the unified statics of some limited-DOF parallel manipulators (PMs) are studied systematically. First, a general PM model is constructed, and the unified inverse displacement is analyzed. Second, various types of acceptable legs are synthesized; the poses of the active/constrained wrench exerted on the various acceptable legs are determined by the observation approach. Third, a unified 6 × 6 Jacobina matrix and a unified statics equation are derived for solving active/constrained wrench of many limited-DOF PMs. Finally, two PMs are presented to illustrate this approach.

This work proposes a strategy for position control and obstacle avoidance in a quadcopter based on constrained generalized predictive control and geometric attitude control. The approach allows real-time trajectory tracking using optimal control actions and avoids collisions with static obstacles whose position is known. An experimental validation of the proposed controller is presented.

Ankle inversion is a common injury of musculoskeletal system among athletes and also in the older population. Investigation into ankle inversion requires quantitative assessment of the smallest amount of height/angle change in the floor that can be perceived by human. Blocks of different thickness have been used to change floor height manually during tests. We aimed to develop an automatic apparatus that is able to provide improved height and angle resolutions for dynamic ankle proprioception. We designed and manufactured a five-bar planar robot with one coupler serving as the mobile platform. We used a stiffening rib to achieve consistent differences in deflection across the workspace of the mobile platform. The reported robot translates at the maximal speed 423 mm/s with a resolution at 0.21 mm under a maximal load of 358 kg. This robot allows for increased sensitivity, which may lead to further investigation of functional proprioceptive ability and reflect finely tuned sensory requirements for upright stance.

This paper addresses the path planning problem for manipulators. The problem of path planning in robotics can be defined as follows: To find a collision free trajectory from an initial configuration to a goal configuration. In this paper a collision-free path planner for manipulators, based on a local constraints method, is proposed. In this approach the task is described by a minimization problem under geometric constraints. The anti-collision constraints are mapped as linear constraints in the configuration space and they are not included in the function to minimize. Also, the task to achieve is defined as a combination of two displacements. The first displacement brings the robot towards to the goal configuration, while the second one allows the robot to avoid the local minima. This formulation solves many of classical problems found in local methods. However, when the robot acts in some heavy cluttered environments, a zig-zaging phenomenon could appear. To solve this situation, a graph based on the local environment of the robot is constructed. On this graph, an A* search is performed, in order to find a dead-lock free position that can be used as a sub-goal in the optimization process. This path-planner has been implemented within SMAR, a CAD-Robotics system developed at our laboratory. Tests in heavy cluttered environments were successfully performed.

This paper presents a two-level control strategy for bipedal walking mechanism that accounts for implicit control of push-off on the between-step control level and tracking of imposed holonomic constraints on kinematic variables via feedback control on within-step control level. The proposed control strategy was tested in a biologically inspired model with minimal set of segments that allows evolution of human-like push-off and power absorption. We investigated controller's stability characteristics by using Poincaré return map analysis in eight simulation cases and further evaluated the performance of the biped walking model in terms of how variations in torso position and gait velocity relate to push-off and power absorption. The results show that the proposed control strategy, with the same set of controller's gains, enables stable walking in a variety of chosen gait parameters and can accommodate to various trunk inclinations and gait velocities in a similar way as seen in humans.

A new minimally invasive surgical (MIS) robot consisting of a spherical remote center motion (RCM) mechanism with modular design is proposed. A multi-objective dimensional synthesis model is presented to obtain the excellent performance indices. There are four objectives: a global kinematic index, a compactness index, a global comprehensive stiffness index, and a global dynamic index. Other indices characterizing the design requirement, such as workspace, mechanical parameter, and mass, are chosen as constraints. A new decoupled mechanism is raised to solve the coupled motion between the linear platform and the four degrees of freedom (DoF) of surgical instrument as a result of post-driving motors. Another new mechanical decoupled method is proposed to eliminate the coupled motion between the wrist and the forceps, enhance the dexterity of surgical instrument, and improve the independence of each motor. Then, a 7-DoF MIS robotic prototype based on optimization results has been built up. Experiment results validate the effectiveness of the two mechanical decoupled methods. The position change of the RCM point, accuracy, and repeatability of the MIS robot meet the requirements of MIS. Successful animal experiments validate the effectiveness of the novel MIS robot.

In this study, we introduce a novel three-dimensional micro-scale robot capable of swimming in low Reynolds number. The proposed robot consists of three rotating disks linked via three perpendicular adjustable rods, actuated by three rotary and three linear motors, respectively. The robot mechanism has an important property which makes it superior to the previously designed micro swimmers. In fact, our goal is designing a micro swimmer which its controllability matrix has full rank and hence it will be capable to perform any desired maneuver in space. After introducing the mechanism and derivation of the dynamical equations of motion, we propose a control method to steer the robot to the desired position and orientation in the presence of external disturbances in the low Reynolds number flow. Simulation results confirm the successful performance of the proposed mechanism and employed control method demonstrating high maneuverability of microrobot.

This article designs a frog-inspired swimming robot based on pneumatic muscles. The musculoskeletal characteristics of the frog are refined and used as the basis for the design of the robot joint structure and movement mode. The posture adjustment module, joint water seal, and power system are designed to meet the robot’s motion requirements, and the structure optimization design of the robot is completed by combining simulation analysis. The body length of the robot is about 710 mm, and the overall mass is 10 kg. Combining the structural characteristics of the robot, the control system is built to realize the frog-like motion. The robot’s propulsion speed is about 0.6 m/s, the propulsion distance reaches 2.4 m, the turning angle is 30°, and the turning radius is 0.6 m. The prototype experiment verifies the rationality of the frog-inspired swimming robot structure design and the reliability of the control system and water seal.

This paper discusses analytical and deterministic models for a plane curve with minimum deformation that may be utilized in planning the motion of elastic linear objects and investigating the inverse kinematics of a hyper-redundant robot. It usually requires intensive computation to determine the configuration of elastic linear objects. In addition, conventional optimization-based numerical techniques that identify the shape of elastic linear objects in equilibrium involve non-deterministic aspects. Several analytical models that produce the configuration of elastic linear objects in an efficient and deterministic manner are presented in this paper. To develop the analytical expressions for elastic linear objects, we consider a cantilever beam where the deflections are determined according to the Euler–Bernoulli beam theory. The deflections of the cantilever beam are determined for prescribed constraints imposed on the deflections at the free end to replicate various elastic linear objects. Deflections of a cantilever beam with roller supports are explored to replicate elastic linear objects in contact with rigid objects. We verify the analytical models by comparing them with exact beam deflections. The analytical model is precisely accurate for beams with small deflections as it is developed on the basis of the Euler–Bernoulli beam theory. Although it is applied to beams undergoing large deflections, it is still reasonably accurate and at least as precise as the conventional pseudo-rigid-body model. The computational demand involved in using the analytical models is negligible. Therefore, efficient motion planning for elastic linear objects can be realized when the proposed analytical models are combined with conventional motion planning algorithms. We also demonstrate that the analytical model solves the inverse kinematics problem in an efficient and robust manner through numerical simulations.

In SLAM (simultaneous localization and mapping), the topological paradigm provides a more natural and compact solution that scales better with the size of the environment. Computer vision has always been regarded as the ideal sensor technology for topological feature extraction and description and several methods have been proposed in the literature, but they are either time-consuming, require plenty of different sensors, or are very sensitive to perceptual aliasing, all of which limit their application scope.

This paper presents a fast-to-compute collection of features extracted from monocular images, and an adaptive matching procedure for location identification in structured indoor environments inspired by the natural language processing field. Although only dominant vertical lines, color histograms, and a reduced number of keypoints are employed in this paper, the matching framework introduced allows for the incorporation of almost any other type of feature. The results of the experiments carried out in a home and an office environment suggest that the proposed method could be used for real-time topological scene recognition even if the environment changes moderately over time. Due to the combination of complementary features, high precision can be achieved within reasonable computation time by using weaker but faster descriptors.

In this paper, a dynamic model of a seven-joints manipulator operated in a zero-g simulation system is established. The errors of the friction, the suspension force, and the flexible deformation of arms are considered. Furthermore, the unloading ratio, which can evaluate the performance of the simulation system, is presented. It can reflect the level of similarity between the system and the space environment directly and effectively. The results of experimental and theoretical analyses verify the correctness of the model. It helps us to get the joint torques when the actual space manipulator without the torque sensor operates in this system and guarantees the safety of the experiments.

We have introduced a new low-Reynolds-number microrobot with high 3D maneuverability. Our novel proposed microrobot has a higher rank of the controllability matrix with respect to the previous microswimmers which makes it capable of performing complex motions in space. In this study, governing equations of the microswimmer’s motion have been derived and simulated. Subsequently, we have proposed a cascade optimal control technique to control the swimmer trajectory. In the proposed control scheme, the actuation is provided in a way that an exponential stability on the system trajectory error as well as minimum fluctuations of control signals are achieved.

In multi-robot assembly of parts, for successful mating, the grasped parts must be located with sufficiently small position and orientation errors so that assembly can be achieved. This paper describes a new approach for determining the absolute three-dimensional spatial location of parts grasped by robots during assembly. Through a combination of robot pose calibration and part-sensor calibration, the robot, used to grasp the part, is calibrated to accurately position and orient parts to a designated mating location. First, by employing a robot pose measurement system, the 6 DOF robot pose errors relative to a reference coordinate frame are compensated. Second, with the implementation of a part pose measurement, the 6 DOF part pose errors, relative to the robot tool frame, are estimated in real time. An experimental verification of the proposed methodology using a single FANUC S–110 robot manipulating an automotive sheet metal part is described.

Operation of tools has long been studied in robotics. Although appropriate hold of the tool by robots is the base of successful tool operation, it is not with ease especially for tools with complicated shape. In this paper, an assist system for a four-limbed robot is proposed for remote operation of reaching and grasping electric drills using deep reinforcement learning. Through comparative evaluation experiments, the increase of success rate for reaching and grasping is verified and the decrease in both physical and mental workload of the operator is also validated by the index of NASA-TLX.

This study is concerned with the tracking control problem for nonlinear uncertain robotic systems in the presence of unknown actuator nonlinearities. A novel adaptive sliding controller is designed based on a robust disturbance observer without any prior knowledge of actuator nonlinearities and system dynamics. The proposed control strategy can guarantee that the tracking error eventually converges to an arbitrarily small neighborhood of zero. Simulation results are included to demonstrate the effectiveness and superiority of the proposed strategy.