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Proper platform pose is important for the mobile manipulator to accomplish dexterous manipulation tasks efficiently and safely, and the evaluation criterion to qualify manipulation performance is critical to support the pose decision process. This paper aims to present a comprehensive index to evaluate the manipulator’s operation performance from various aspects.

In this research, a criterion called hybrid manipulability (HM) is proposed to assess the performance of the manipulator’s operation, considering crucial factors such as joint limits, obstacle avoidance and stability. The determination of the optimal platform pose is achieved by selecting the pose that maximizes the HM within the feasible inverse reachability map associated with the target object.

A self-built mobile manipulator is adopted as the experimental platform, and the feasibility of the proposed method is experimentally verified in the context of object-grasping tasks both in simulation and practice.

The proposed HM extends upon the conventional notion of manipulability by incorporating additional factors, including the manipulator’s joint limits, the obstacle avoidance situation during the operation and the manipulation stability when grasping the target object. The manipulator can achieve enhanced stability during grasping when positioned in the pose determined by the HM.

The current methods for inspecting tall or deep structures such as towers, chimneys, silos, and wells suffer from certain constraints. Manual and assisted inspection methods including humans, drones, wall climbing robots, and others are either costly, have a limited operation time, or affected by field conditions, such as temperature and radiation. This study aims to overcome the presented challenges through a teleoperated soft continuum manipulator capable of inspecting tall or deep structures with high resolution, an unlimited operation time and the ability to use different arms of the manipulator for different environments and structure sizes.

The teleoperated manipulator uses one rotary and two tendon actuators to reach and inspect the interior of a tall (or deep) structure. A sliding part along the manipulator’s body (arm constrainer and tendon router) induces a variable-length bending segment, allowing an inspection camera to be placed at different distances from the desired location.

The experiments confirmed the manipulator’s ability to inspect different locations in the structure’s interior. The manipulator also demonstrated a submillimeter motion resolution vertically and a 2.5 mm per step horizontally. The inspection time of the full structure was 48.53 min in the step-by-step mode and was calculated to be 4.23 min in the continuous mode.

The presented manipulator offers several design novelties: the arm’s thin-wide cross-section, the variable-length bending segment in a fixed-length body, the external rolling tendon routing and the ability to easily replace the arm with another of different material or dimensions to suite different structures and environments.

This paper aims to develop a new robotic ultrasound system for spine imaging with more anthropomorphic scanning manipulation in comparison with previously reported techniques.

The system evaluates the imaging quality of ultrasound (US) B-scans by detecting vertebral landmarks and groups the images with relatively low quality into several sub-optimal types. By imitating the scanning skills of sonographers, the authors defined a set of adjustment strategies for certain sub-optimal types. In this way, the robot can recollect the US images with high quality by adaptively adjusting the pose of the probe like a sonographer.

The results from phantom experiments and in vivo experiments showed that the proposed method could improve the quality of B-scans during the scanning. The 3 D US volume reconstruction has also verified the feasibility of the proposed method.

This paper demonstrates how to adapt a robotic spinal ultrasound scanning using a preliminary anthropomorphic approach.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

This paper aims to present an iterative path-following method with joint limits to solve the problem of large computation cost, movement exceeding joint limits and poor path-following accuracy for the path planning of hyper-redundant snake-like manipulator.

When a desired path is given, new configuration of the snake-like manipulator is obtained through a geometrical approach, then the joints are repositioned through iterations until all the rotation angles satisfy the imposed joint limits. Finally, a new arrangement is obtained through the analytic solution of the inverse kinematics of hyper-redundant manipulator. Finally, simulations and experiments are carried out to analyze the performance of the proposed path-following method.

Simulation results show that the average computation time is 0.1 ms per step for a hyper-redundant manipulator with 12 degrees of freedom, and the deviation in tip position can be kept below 0.02 mm. Experiments show that all the rotation angles are within joint limits.

Currently , the manipulator is working in open-loop, the elasticity of the driving cable will cause positioning error. In future, close-loop control based on real-time attitude detection will be used in in combination with the path-following method to achieve high-precision trajectory tracking.

Through a series of iterative processes, the proposed method can make the manipulator approach the desired path as much as possible within the joint constraints with high precision and less computation time.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

This paper aims to study using a mobile manipulator with a collaborative robotic arm component to manipulate objects beyond the robot’s maximum payload.

This paper proposes a single-short probabilistic roadmap-based method to plan and optimize manipulation motion with environment support. The method uses an expanded object mesh model to examine contact and randomly explores object motion while keeping contact and securing affordable grasping force. It generates robotic motion trajectories after obtaining object motion using an optimization-based algorithm. With the proposed method’s help, the authors plan contact-rich manipulation without particularly analyzing an object’s contact modes and their transitions. The planner and optimizer determine them automatically.

The authors conducted experiments and analyses using simulations and real-world executions to examine the method’s performance. The method successfully found manipulation motion that met contact, force and kinematic constraints. It allowed a mobile manipulator to move heavy objects while leveraging supporting forces from environmental obstacles.

This paper presents an automatic approach for solving contact-rich heavy object manipulation problems. Unlike previous methods, the new approach does not need to explicitly analyze contact states and build contact transition graphs, thus providing a new view for robotic grasp-less manipulation, nonprehensile manipulation, manipulation with contact, etc.

This paper aims to present a kinematics analysis method and statics based control of the continuum robot with mortise and tenon joints to achieve better control performance of the robot.

The kinematics model is derived by the geometric analysis method under the piecewise constant curvature assumption, and the workspace and dexterity of the proposed robot are analyzed to optimize its structure parameters. Moreover, the statics model is established by the principle of virtual work, which is used to analyze the mapping relationship between the bending deformation and the applied forces/torques. To improve the control accuracy of the robot, a model-based controller is put forward.

Results of the experiments verify the feasibility of the proposed continuum structure and the correctness of the established model and the control method. The force deviation between the theoretical value and the actual value is relatively small, and the mean value of the deviation between the driving forces is only 0.46 N, which verify the established statics model and the controller.

The proposed model and motion controller can realize its accurate bending control with a few deviations, which can be used as the reference for the motion planning and dynamic model of the continuum robot.

In the digital assembly system of large aircraft components (LAC), the docking trajectory of LAC is an important factor affecting the docking accuracy and stability of the LAC. The main content of docking trajectory planning is how to move the LAC from the initial posture and position to the target posture and position (TPP). This paper aims to propose a trajectory planning method of LAC based on measured data.

First, the posture and position error model of the wing is constructed according to the measured data of the measurement points (MPs) and the fork lug joints. Second, the particle swarm optimization algorithm based on the dynamic inertia factor is used to optimize the TPP of the wing. Third, to ensure the efficiency and stability of posture adjustment, the S-shaped curve is used as the motion trajectory of LAC, and the parameters of the trajectory are solved by the generalized multiplier method. Finally, a series of docking experiments are carried out.

During the process of posture adjustment, the motion of the numerical control locator (NCL) is stable, and the interaction force between the NCLs is always within a reasonable range. After the docking, the MPs are all within the tolerance range, and the coaxiality error of the fork lug hole is less than 0.2 mm.

In this paper, the measured data rather than the theoretical design model is used to solve the TPP, which improves the docking accuracy of LAC. Experiment results show that the proposed trajectory method can complete the LAC docking effectively and improve the docking accuracy.

This paper aims to present a novel lightweight distribution grid operating robot system with focus on lightweight and multi-functionality, aiming for autonomous and live-line maintenance operations.

A ground-up redesign of the dual-arm robotic system with 12-DoF is applied for substantial weight reduction; a dual-mode operating control framework is proposed, with vision-guided autonomous operation embedded with real-time manual teleoperation controlling both manipulators simultaneously; a quick-swap tooling system is developed to conduct multi-functional operation tasks. A prototype robotic system is constructed and validated in a series of operational experiments in an emulated environment both indoors and outdoors.

The overall weight of the system is successfully brought down to under 150 kg, making it suitable for the majority of vehicle-mounted aerial work platforms, and it can be flexibly and quickly deployed in population dense areas with narrow streets. The system equips with two dexterous robotic manipulators and up to six interchangeable tools, and a vision system for AI-based autonomous operations. A quick-change tooling system ensures the robot to change tools on-the-go without human intervention.

The resulting dual-arm robotic live-line operation system robotic system could be compact and lightweight enough to be deployed on a wide range of available aerial working platforms with high mobility and efficiency. The robot could both conduct routine operation tasks fully autonomously without human direct operation and be manually operated when required. The quick-swap tooling system enables lightweight and durable interchangeability of multiple end-effector tools, enabling future expansion of operating capabilities across different tasks and operating scenarios.