For wheeled mobile robots moving in rough terrains or uncertain environments, driving failure will be encountered when trafficability failure occurs. Continuous mobility of mobile robots with special ability for overcoming driving failure on rough terrain has rarely been considered. This study was conducted using a four-wheel-steering and four-wheel-driving mobile robot equipped with a binocular visual system. First, quasi-static force analysis is carried out to understand the effects of different driving-failure modes on the mobile robot while moving on rough terrain. Secondly, to make the best of the rest of the driving force, robot configuration transformation is employed to select the optimal configuration that can overcome the driving failure. Thirdly, sliding mode control based on back-stepping is adopted to enable the robot achieve continuous trajectory tracking with visual feedback. Finally, the efficacy of the presented approach is verified by simulations and experiments.

This paper presents a geometrical alternative to estimate the accuracy of a deployable mechanism equipped on the Synthetic Aperture Radar (SAR) space satellite. The deployable mechanism is simplified into a planar mechanism, and the error space of the outer panel in its deployed state is modeled concerning multiple revolute joint clearances and link length tolerances. Compared with the existing methods, the advance of the proposed geometrical approach lies in that it gives expressions of the complete error mobility that the outer panel may have. After deducing the expressions, the final error space is visualized and evaluated numerically with discrete sampling points. Finally, based on the error space and the computed maximum errors, effects of tolerances on accuracy are studied and the optimal accuracy design of tolerances is obtained. The result reveals that, for the deployable mechanism discussed in this paper, effects of tolerances on the final accuracy can be eliminated without increasing the manufacturing cost.

A 10 kV distribution network is critical for ensuring power supply to residents and factories. The number of power maintenance operations is rapidly increasing, and aerial cable stripping is a significant branch of these routine maintenances. High-voltage cable stripping, on the other hand, is mostly done manually, which is inefficient and poses serious security risks. As a result, this paper proposes an automatic wire stripping robot for use in a 10 kV power grid. The mechanical structure of the stripping robot is designed for installation on the insulating rod based on the working environment of 10 kV overhead cables. The robot was subjected to electromagnetic field simulation, modal analysis, and rigid-flexible coupling analysis. Finally, the robot prototype is built, and the PID controller is designed. Stripping tests are performed on a cable with a cross-sectional area of 95, 120, 150, 240, and 300 mm2, and the results are satisfactory.

This paper presents an integrated optimal control framework for velocity and steering control of an autonomous pursuit vehicle, where the control objectives satisfy the requirements of collision avoidance and moving target tracking. A distinctive feature of the proposed velocity and steering control is the application of logarithmic penalty functions to both. The control barrier imposed by logarithmic function provides a unique tool in computing a balanced trajectory with optimal tracking error, control effort and safety margin. Trajectories compliant with the safety regulations for autonomous driving have been planned based on estimated intention of the target and the obstacles. Effects of the controller weights have been extensively simulated to assess the performance of the proposed strategy in a variety of dynamic situations. The controller has been validated on a real-life robot by using a shrinking horizon control policy for iterative optimisation.

This paper addresses logarithmic quantizers with dynamic sensitivity design for continuous-time linear systems with a quantized feedback control law. The dynamics of state quantization and control quantization sensitivities during “zoom-in”/“zoom-out” stages are proposed. Dwell times of the dynamic sensitivities are co-designed. It is shown that with the proposed algorithm, a single-input continuous-time linear system can be stabilized by quantized feedback control via adopting sensitivity varying algorithm under certain assumptions. Also, the advantage of logarithmic quantization is sustained while achieving stability. Simulation results are provided to verify the theoretical analysis.

The repetitive motion planning movements of the redundant manipulator will cause oscillations and unintended swings of joints, which increase the risk of collisions between the manipulator and its surroundings. Motivated by this phenomenon, this paper presents an inverse kinematics algorithm for the spherical-revolute-spherical manipulator to solve the paradox raised by joint-drift and control the pose with no swing of the elbow. This algorithm takes the joint Cartesian positions set as the intermediary and divides the inverse solution process into two mapping processes within joint limits. Simulations are executed to evaluate this algorithm, and the results show this algorithm is applicable to repetitive motion planning and is capable of producing superior configurations based on its real-time ability and stable solve rate. Experiments using the 7-degree-of-freedom spherical-revolute-spherical manipulator demonstrate the effectiveness of this algorithm to remedy the joint-drift and elbow swing compared to Kinematics and Dynamics Library and TRAC-IK.

This paper presents a novel microstep control approach for improving the positioning precision of a millimeter-sized omni-directional mobile microrobot. The microrobot that is designed for microassembly in a microfactory is driven by three electromagnetic micromotors. The structures of both the microrobot and the micromotor are described in the paper. The torque vectors synthesis method (TVSM) is developed and the torque self-balance principle (TSBP) is employed to realize the microstep control. The control circuit that needs a complex digital logic is devised with a complex programmable logic device (CPLD). The experiments using a hard disk and the real microrobot demonstrated the validity and performance of TVSM and TSBP. And the angular step precision of the microrobot is increased by three times compared to the normal control.

We constructed a high reliability parts-picking device with an active and multi-sensor visual system, that picks up a part from randomly stacked parts. The system determines the orders in which to pick up the parts. To determine the order, we introduce concepts of risks of collapsing a stack by picking, and the ease of manipulator operations. The system examines if the risks exist and estimates the ease. We show that the parts-picking system can achieve high reliability by determining the orders, using the effects of the examination and the estimation. We also give some experimental results.

Robotic swimmers are currently a subject of extensive research and development for several underwater applications. Clever design and planning must rely on simple theoretical models that account for the swimmer’s hydrodynamics in order to optimize its structure and control inputs. In this work, we study a planar snake-like multi-link swimmer by using the “perfect fluid” model that accounts for inertial hydrodynamic forces while neglecting viscous drag effects. The swimmer’s dynamic equations of motion are formulated and reduced into a first-order system due to symmetries and conservation of generalized momentum variables. Focusing on oscillatory inputs of joint angles, we study optimal gaits for 3-link and 5-link swimmers via numerical integration. For the 3-link swimmer, we also provide a small-amplitude asymptotic solution which enables obtaining closed-form approximations for optimal gaits. The theoretical results are then corroborated by experiments and motion measurement of untethered robotic prototypes with three and five links floating in a water pool, showing a reasonable agreement between the experiments and the theoretical model.

In this work, we present a continuous observer and continuous controller for a multiple degree of freedom robot manipulator with hysteretic joint friction. The fictitious hysteresis state is of course unknown to the controller and must be estimated. The joint velocities are assumed measured here. For this considered plant, we propose and present a continuous observer/controller that estimates or observes the hysteresis state and drives the position tracking error to zero. We prove that the combined tracking error and observer error converges to zero globally exponentially.

In the human body there are many joints whose functions are very similar to revolute joints. To avoid the complexity of these joints, they are usually substituted by revolute joints in many humanoid robots. Revolute joints have purely rotational motion along their fixed axis, while real joints in the human body have Instantaneous Rotational Axis (IRA) due to their configuration. Substitution of this kind of human joints with revolute (hinge) joints in robots changes the kinematics of joints. Knowing the exact characteristics of the moving axis of rotation in human joints is a prerequisite for the kinematic study of a joint. Here the main geometrical difference between these kinds of joints in humans and their simplified (hinge-like) models in robots is described. Then, as a case study, the mechanism of the three joints of the index finger are compared with their hinge-like model using a multi-body code to understand when revolute joints can be substituted for anthropometric joints in hand exoskeletons and robotic hands. Furthermore, the position of IRA and its distance from the center of the condyle of the joint are presented. The concept and the results can be extended for other fingers and all similar joints, and can be used in humanoid robots, hand exoskeletons and robotic hands.

In this paper, the robust adaptive control and observer are considered for a pneumatic robot leg. This approach does not require a precise knowledge of the robot model physical parameters, only the adaptive upper bounds on the norm of the matrices model are used, which with the sliding mode guarantee the robustness of system. Convergence conditions and simulation results for the adaptive control and observer are presented.

This paper presents an absolute position estimation system for a mobile robot moving on a flat surface. In this system, a 3-D landmark with four coplanar points and a non-coplanar point is utilized to improve the accuracy of position estimation and to guide the robot during navigation. Applying theoretical analysis, we investigate the image sensitivity of the proposed 3-D landmark compared with the conventional 2-D landmark. In the camera calibration stage of the experiments, we employ a neural network as a computational tool. The neural network is trained from a set of learning data collected at various points around the mark so that the extrinsic and intrinsic parameters of the camera system can be resolved. The overall estimation algorithm from the mark identification to the position determination is implemented in a 32-bit personal computer with an image digitizer and an arithmetic accelerator. To demonstrate the effectiveness of the proposed 3-D landmark and the neural network-based calibration scheme, a series of navigation experiments were performed on a wheeled mobile robot (LCAR) in an indoor environment. The results show the feasibility of the position estimation system applicable to mobile robot's real-time navigation.

The use of ultrasonic range transducers is an inexpensive method of obtaining information about the environment surrounding a robotic System. However, ultrasonic ranging suffers from various shortcomings, one of the major being the production of unreliable data caused by specular reflection.

This work presents an original approach to overcoming the problem of unreliable ultrasonic range data which is caused by specular reflection of the ultrasonic beam. The approach is shown to discriminate between reliable and unreliable data, thus enhancing the role of the ultrasonic range transducer in robotic applications.

This article focuses on the luggage trolley transportation problem, an essential part of robotic autonomous luggage trolley collection. To efficiently address the nonholonomic constraints derived from the formation of two collaborative robots and a queue of luggage trolleys, we propose a comprehensive framework consisting of a global planning method and a real-time divide-and-conquer control strategy. The popular Hybrid A* algorithm generates a feasible path as the global planner. A model predictive controller is designed to track this path stably and in real time. To maintain the formation so that the whole queue of robots and luggage trolleys does not split, a safety filter that consists of a discrete-time control Lyapunov function and a decentralized control barrier function is implemented in the transportation process. Finally, we conduct real-world experiments to verify the effectiveness of the proposed method on three representative paths, and the results show that our approach can achieve robust performance. The demonstration video can be found at https://www.youtube.com/watch?v=iPiT8BfLIpU.

Unmanned aerial vehicles (UAVs) possess fast-moving abilities and have been used in various tasks in the past decades. However, their performances are still restricted by insufficient endurance and confined environments. Intuitively, combining other locomotion modes with UAVs, such as diving and driving, would be an appropriate idea to improve the robot’s adaptability and solve the endurance problem. Recently, the terrestrial/aerial hybrid robots have drawn the researchers’ eyes for their outstanding performances, which can deploy flight mode to traverse insurmountable terrains and ground mode to increase endurance and realize detailed searches. Therefore, this paper developed the autonomous quadrotor tilting hybrid robot (AQT-HR) to achieve terrestrial/aerial dual-modal mobility and verified that the robot delivers high energy efficiency. The AQT-HR can achieve flying and driving through a quadrotor tilting mechanism, which can alter one single driving force into different directions. Furthermore, the dynamic models of the hybrid robot’s aerial and ground locomotion are derived and introduced into the model-feedforward PID control algorithm for improving the robot’s flying stability. Finally, we conducted some mobility tests and experiments about traversing obstacles to demonstrate that the proposed hybrid robot can realize autonomous mode switching and perform a low energy consumption in ground movement mode.

In this paper, an automatic obstacle avoidance trajectory planning strategy is proposed for the simultaneous motion of multi-robots, which perform anthropomorphic skill operations in a large curved preformed three-dimensional (3D) weaving environment with multiple obstacles and limited space, to eliminate tedious manual calibration work of robot path in engineering. Firstly, an Adaptive Goal-guided Rapidly-exploring Random Trees (AGG-RRT) algorithm is proposed, combined with the robot obstacle avoidance strategy, to search the discrete position of the collision-free path of the end-effector gradually from the starting point to the ending point. Then the optimization of the path is completed by bidirectional pruning of redundant nodes and cubic non-uniform rational B-spline (NURBS) curve fitting. And finally, the robot trajectory is interpolated based on S-shaped acceleration/deceleration planning to ensure smooth robot joint motion. The simulation results demonstrate the superiority of the AGG-RRT algorithm over the basic RRT algorithm and related improved algorithms in terms of search time and success rate. The simulated experiments also achieve the smooth trajectory planning of multiple robotic arms with the synchronous obstacle avoidance motion, which shows that the AGG-RRT algorithm is successfully applied and the collision-free trajectory planning strategy is effective.