A cable-driven segmented manipulator (CDSM) has considerable potential in narrow space operations because it has a slender and light body with flexible mobility. However, the existing CDSM segment driving mechanisms are coupled to each other. The driving distance of the rear segment cable is superimposed with that of the front segment cable, which renders the cables’ drive distance inconsistent. Moreover, the system kinematics, dynamics, and control become extremely complex. In this article, a novel decoupling driving mechanism is proposed to solve the coupling problem, simplifying the modeling and control of the CDSM. The routing of the driving cable is designed based on the characteristics of the symmetrical offset (i.e., the same magnitude but opposite in direction) of the cable length applicable to joints with one and two degrees of freedom. By modifying the direction of the driving cable in the middle of the proximal segment, the driving cable length of the distal segment is unaffected by the change of the angle of the front segment. Moreover, to increase the drive stroke, a multiturn winding mechanism is designed, reducing the volume and mass of the driving box. Accordingly, an improved forward and backward reaching inverse kinematics is proposed for CDSM based on virtual joints. Compared with the Jacobian pseudo-inverse method, the computational efficiency is improved. Finally, the proposed mechanisms and methods are verified via a CDSM prototype. The results indicate that the proposed manipulator compared with typical manipulators has larger movement range, higher end velocity, and guaranteed accuracy due to the proposed decoupled driving and fast kinematics resolution.

This paper investigates one of the most challenging tasks in dynamic manipulation-catching large-momentum moving objects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the robot's capability of interacting with its surrounding environment. Yet, the inevitable motion mismatch between the fast moving object and the approaching robot will result in large impulsive forces, which lead to the unstable contacts and irreversible damage to both the object and the robot. To address the above problems, we propose an online optimization framework to: 1) estimate and predict the linear and angular motion of the object; 2) search and select the optimal contact locations across every surface of the object to mitigate impact through sequential quadratic programming (SQP); 3) simultaneously optimize the end-effector motion, stiffness, and contact force for both robots using multi-mode trajectory optimization (MMTO); and 4) realise the impact-aware catching motion on the compliant robotic system based on indirect force controller. We validate the impulse distribution, contact selection, and impactaware MMTO algorithms in simulation and demonstrate the benefits of the proposed framework in real-world experiments including catching large-momentum moving objects with welldefined motion, constrained motion and free-flying motion.

This paper introduces a novel task-space decomposed motion planning framework for multi-robot simultaneous locomotion and manipulation. When several manipulators hold an object, closed-chain kinematic constraints are formed, and it will make the motion planning problems challenging by inducing lower-dimensional singularities. Unfortunately, the constrained manifold will be even more complicated when the manipulators are equipped with mobile bases. We address the problem by introducing a dual-resolution motion planning framework which utilizes a convex task region decomposition method, with each resolution tuned to efficient computation for their respective roles. Concretely, this dual-resolution approach enables a global planner to explore the low-dimensional decomposed task-space regions toward the goal, then a local planner computes a path in high-dimensional constrained configuration space. We demonstrate the proposed method in several simulations, where the robot team transports the object toward the goal in the obstacle-rich environments.

The transition from free motion to contact is a challenging problem in robotics, in part due to its hybrid nature. Additionally, disregarding the effects of impacts at the motion planning level often results in intractable impulsive contact forces. In this paper, we introduce an impact-aware multi-mode trajectory optimization (TO) method that combines hybrid dynamics and hybrid control in a coherent fashion. A key concept is the incorporation of an explicit contact force transmission model in the TO method. This allows the simultaneous optimization of the contact forces, contact timings, continuous motion trajectories and compliance, while satisfying task constraints. We compare our method against standard compliance control and an impact-agnostic TO method in physical simulations. Further, we experimentally validate the proposed method with a robot manipulator on the task of halting a large-momentum object.

For traditional manipulators, there is a large number of electrical cables between the motion controller and the joint servo controllers. It is very inconvenient for maintenance, update, and safe operation. In this paper, we develop a lightweight redundant manipulator with high stable wireless communication link and compliance control. The motion controller, servo controller, and communication link are taken as a whole system to be optimized. The manipulator body and the motion controller are physically separated. It is very helpful for building distributed networked-manufacturing system or intelligent manufacturing system for Industry 4.0. The control system can be quickly updated by changing the object's identification without reconnect the communication cables. The mechanical part of the manipulator contains modular joints and links. Each joint is integrated with hall sensors, an incremental magnetic encoder, an absolute magnetic encoder and current sensors. The electrical part includes a central controller, seven joint servo controllers, and a wireless communication module based on ZigBee. By designing the application layer protocol, the communication stability is improved. In order to achieve the force control requirements in fine operation like assembly. A wireless compliance control frame is then designed. The compliance control method is realized on the central controller, by which the generated control commands are sent to the joint servo controllers through a wireless link. The problems caused by large electrical cables are then solved. Finally, the prototype and the experimental system are developed. Some experiments are carried out, including wireless communication test, trajectory tracking experiments, load carrying experiments, and wireless impedance control experiments. Results verify the functions and performance of the developed 7-DOF manipulator.

Capturing a moving object with large momentum by a dual-arm robot is especially challenging because of the requirement of dual-arm coordinated motion planning for tracking the moving object, and the operational force control for contact and momentum transfer. In this paper, we present a dual-arm coordinated motion planning and compliance control method with a unique null-space projected relative Jacobian and relative operational force between the two arms. The proposed method is able to plan dual-arm capturing motion and control the capturing force without disturbing the tracking motion. We have also adopted a direct collocation trajectory optimization method to generate optimal trajectory to decrease the object's momentum with minimum effort. Simulation and experiment of dual-arm robots picking up a moving box on a mobile platform are carried out to verify the proposed method.

In this paper, we developed a small wheel-legged mobile robot system, which could walk on different road environments using wheels or legs. It is composed of mechanical, sensor and control subsystems. The mechanical subsystem includes a wheel-legged mobile platform, a rigid robotic arm and a flexible arm. The mobile platform provides a variety of movement ways to meet the requirement of different mobility. The rigid arm (denoted by arm-a) is a serial manipulator with 4-DOFs. It can be used to grasp and manipulate payloads. The flexible arm (denoted by arm-b) is a manipulator with continuous curve, and a camera is mounted on arm-b. So it can be used to provide visual inspection and measurement information. The sensor subsystem is composed of ultrasonic sensors mounted on the platform and a WIFI camera mounted on arm-b. It provides measurement information and visual inspection for remote control. The control subsystem includes an embedded controller and a PC computer. The former is developed based on an ARM microprocessor, on which the real-time operation system-RT-Thread system runs. The mission decomposition and trajectory planning algorithms are programed in C language and run in the PC. At last, typical experiments are performed. Experiment results verified the robot's mobility, operation capability and remote-control function.

With the rapid development of robotics, dual-arm robots have been more and more widely used. Compared with the traditional single manipulator, it is very challenging for a dual-arm robot in modelling, planning and control. In this paper, we propose two compliance control methods for dual arm coordination to meet different requirements of fine manipulation tasks, such as payload carrying, assembly and repairing. The first method is called master-slave force control strategy, and the second is shared force control strategy. For the former, the desired trajectory and operational force of master arm are given in advance. Then that of slave arm are calculated from the closed-chain constraint equation. On the contrary, the two arms can be controlled in shared mode, that is to say, the desired trajectory and operational force of the end-effectors of dual arms are decomposed from the closed-chain constraint equation directly. The coordinated kinematic and dynamic equations of dual-arm robot system are established by considering the closed-chain constraint relationship. According to the force balance equation of the objective payload, the common force is decomposed into the desired end-effector force of each manipulator. Finally, the control algorithms are verified by simulation and experiment.

Due to the dynamic interaction, the motion of the arms alters the attitude and position of the base. To stabilize the centroid position of the base during on-orbital manipulation, we proposed the modeling concept of the "Base Centroid Virtual Manipulator (BCVM)" for free-floating multi-arm space robotic systems. Correspondingly, the trajectory planning method of the balance arm was addressed. The movement direction and the position of each joint of the BCVM are the same as those of the real space manipulator (SM). The end-effector's position of the BCVM denotes the equivalent centroid of the corresponding SM. By resolving the position-level kinematic equations, the singularity-free trajectory of the balance arm was then planned. Based on the BCVM model, the stabilization ability of a given balance arm can be easily determined by analyzing the workspace of the BCVM. Furthermore, the configuration and the mass properties of the balance arm can be optimized. Simulation results of joint trajectory tracking task verified the proposed model and method.

The arm-angle was often used to parameterize the self-motion of S-R-S (Spherical-Revolute-Spherical) redundant manipulators when solving the inverse kinematics. However, there were some shortcomings for previous works: existing algorithm singularity or not suitable for configuration control. In this paper, we proposed an analytical resolution method based on dual arm-angle parameterization. Using two orthogonal vectors to define two absolute reference planes, we got two arm-angles which satisfy a specific condition. Since there is always at least one arm angle to represent the redundancy, the algorithm singularity problem does not exist. The “dual arm-angle” method keeps the advantages of “arm-angle”, and overcomes the shortcomings of the traditional methods. Another contribution of this paper is that we derived the absolute reference elbow attitude matrix0R3ψ=0, which is the key for the analytical inverse kinematics resolution but was not addressed in the previous paper. Simulation results for a general case and an algorithm singularity case verified the presented method.