This paper explores the optimal consensus problem involving fully actuated Euler-Lagrange systems with parametric uncertainties. We propose a distributed adaptive control algorithm that incorporates a novel dynamical auxiliary system to generate reference positions. Nonlinear transformation functions for the position tracking error, along with smooth compensating terms, are introduced and integrated into the reference velocity design. The proposed control framework is distinctive in that it only requires relative position measurements from neighboring agents and does not rely on any global information, thus enabling a fully distributed implementation. A theoretical analysis demonstrates that the proposed control protocol ensures the asymptotic convergence of all agents to the optimal solution of the total cost function and the boundedness of all closed-loop signals. Simulation results for two-link revolute joint manipulators are presented to validate the effectiveness of the proposed approach.

SLAM (Simultaneous Localization and Mapping) has a wide application prospect in navigation of autonomous endoscopic minimally invasive surgery. However, traditional methods like ORB-SLAM2 often struggle in dynamic environments and exhibit significant modeling inaccuracies, particularly in bronchial scenes where respiratory motion induces continuous deformation of the airway structure. To address this challenge, we propose a novel monocular SLAM-based framework for dynamic bronchial environment reconstruction tailored to robotic lung invasive surgery. Firstly, a pseudo-static processing method that builds map sequences at identical respiratory phases across cycles was built. Furthermore, we present a voxel model optimization technique using curvature-consistent graph interpolation to refine the bronchial lumen surface, eliminating pores and redundancies in the voxel map. Experiments conducted on real patient demonstrate that our method has good accuracy and robustness. Compared to existing state-of-the-art methods, our framework achieves superior reconstruction completeness, showing strong potential for clinical use in robotic bronchoscopy.

To address complex mission tasks, multirotors benefit from in-flight reconfiguration that enhances their morphological adaptability. This paper presents the Center-Driven Scissor Extendable Airframe (CDSEA), a novel one-degree-of-freedom (DOF) morphing airframe designed to replace traditional fixed-size airframes. The CDSEA allows a quadrotor to achieve significant morphological changes during flight, with rotors deploying radially from a central point. This capability facilitates substantial variations in footprint radius and ensures smooth transitions. The paper details the mechanical design, as well as kinematic and dynamic analyses, and discusses the actuator selection strategy for the CDSEA. Experimental results with a prototype demonstrate that the CDSEA achieves a footprint-radius deformation ratio of 2.5 and a morphing time of 0.3 seconds, surpassing existing solutions. Additionally, the design improves obstacle avoidance and wind resistance. These results underscore the CDSEA's potential as an advanced solution for enhancing UAV adaptive navigation performance in complex environments.

In this work, a multimodal point cloud registration method using CT and video frames is proposed to optimize the modeling of the bronchial cavity environment. Preoperative CT data improve the quality of point clouds acquired from intraoperative video frames. Initially, preoperative CT scans are used to obtain bronchial point clouds and airway centerlines, while intraoperative bronchial point clouds and endoscope trajectories are captured in real-time using SLAM. Given that intraoperative frame-by-frame mapping cannot be directly globally registered, multi-modal point clouds undergo local segmentation. Subsequently, the preoperative bronchial airway centerlines guide iterative scaling and adjustment of the preoperative CT point clouds, achieving precise registration between the CT and the video frame point clouds. Experimental results demonstrate a rapid and accurate enhancement in the quality of the intraoperative bronchial point cloud, providing more precise maps of the cavity environment for surgical robots. The method is validated and evaluated using CT and video frame data collected from ex vivo pig lungs, achieving intraoperative mapping accuracy of 0.5 millimeter, respectively. These results surpass those of methods relying solely on SLAM for intraoperative mapping.

Improving motion speed and efficiency remains a critical challenge in snake robots gait control. This paper introduces the Loop gait, a novel locomotion gait designed to enhance both speed and energy efficiency of snake robots without passive wheels. Compared to Crawler gait and S-pedal gait, which are more widely used, the Loop gait has a better motion speed (1.8 times of the Crawler gait in the same parameter) and a better motion efficiency (1.6 times of the Crawler gait in the same parameter) due to its more loop body morphology. A static stability model is developed to guide parameter optimization, addressing potential instability caused by elevated center of mass of snake robots. Experiments confirm the Loop gait’s exceptional energy efficiency and propulsion, validating the static stability model’s utility in selecting parameters.

A new control pipeline has been proposed for the Rope-Base Soft-tip Manipulator (RBSM) to execute the surface contact task to prevent the jamming and slipping problems. The control pipeline enables smooth surface-to-surface contact for the RBSM using only force sensors, eliminating the dependence on additional pose measurement of the window surface plane and soft-tip deformation information. The pipeline consists of three steps: free contact step implemented by an exponential force shape controller to avoid force overshoot to the window surface; orientation refinement step implemented by a force and torque combined controller to make the RBSM cleaning head surface stable adapt to the smooth window surface; and finally, a release normal force step to reduce head jamming and region covering with a pre-defined vibration-less cleaning trajectory for smooth cleaning on the slippery window surface. The proposed pipeline has been validated in a Rope base Cleaning Manipulator prototype to clean a common window surface. The force and velocity curves during the cleaning experiment show that the proposed method achieves smooth scraping and cleaning under unknown initial significant errors in surface orientation.

This paper addresses the consensus issue of multiagent systems with both input amplitude and rate constraints. We propose simple yet effective distributed control algorithms that integrate a velocity damping term with nonlinear saturated functions for both undirected and directed graphs. Leveraging the interplay between Barbalat’s lemma and graph theory, we show that all agents can achieve consensus without violating predefined input amplitude and rate constraints through the presented control algorithms. Moreover, we employ the developed framework to solve the rendezvous control problem of quadrotor unmanned aerial vehicles (UAVs) with motion limits. To illustrate and validate our proposed approach, we conduct extensive simulations and comparative experiments. Note to Practitioners—Most existing control methods for multiagent systems achieve consensus but neglect the constraints on the amplitude and rate of the control signal. However, in practice, the control signals are invariably subject to limitations in their amplitude and rate due to factors such as actuator saturation, considerations for ride comfort, and actuator wear. This neglect leads to a degradation in system performance and in severe cases results in the loss of closed-loop stability. This work primarily focuses on developing new control methods that can achieve consensus without violating the predefined input amplitude and rate limitations. The experiments on rendezvous control of quadrotor UAVs show the practical applicability of the presented algorithms, which yield satisfactory control performance as verified by theoretical analysis. This research contributes to the advancement of distributed control for multiagent systems, particularly in scenarios where input constraints are a critical consideration.

The work in this paper delves into the challenge of whole elongated body's obstacle avoidance during path following for a class of bionic snake robots. Currently, most studies focus solely on preventing the robot's head from colliding with obstacles through designed controllers. However, due to the unique elongated structure and biomimetic locomotion modes of snake robots, it is unavoidable that the rest of the robot's body could still collide with obstacles. To resolve this problem, we propose a novel real-time optimization obstacle avoidance strategy for a class of terrestrial snake robots with multi-link elongated body using model predictive control (MPC). Moreover, by leveraging the elongated body characteristics of the robot, an improved path guidance strategy is also developed. The effectiveness of the proposed strategies is verified and validated through extensive simulations and experiments on a custom-built nine-link elongated snake robot. The results demonstrate that all links of the robot can well avoid obstacles while continuing to track the given path.

This article studies the tracking control of a quadrotor unmanned aerial vehicle (UAV) under time-varying external disturbances. An event-triggered sliding mode control (SMC) strategy is proposed by introducing a new triggering condition form of desired trajectory, quadrotor position, and velocity. In the sense of Lyapunov theory, the stability of the entire closed-loop control system is analyzed, and it is proved that the tracking error is adjusted to an adjustable set around zero. We show that the Zeno phenomenon can be avoided; that is, a positive minimum inter-event time is assured. One of the salient features of the proposed strategy is that it can reduce the update frequency of the control efforts, thereby ensuring desirable tracking performance under limited communication bandwidth. Comparative simulation and experimental results are provided to show the efficacy of our framework.

Sanding is a common yet important task in the manufacturing of many wooden objects (e.g. furniture, decoration box), where the coated layer attached on objects is removed after the interaction with sanding belts. Existing sanding operation is heavily dependent on manual works, which is highly labor-intensive and with the low consistency of quality, and the issues of safety and health also arise after continuous working in the noisy and dusty environment. To deal with the aforementioned, this paper presents the development of a new autonomous sanding robot. The autonomous capability of the developed robot is reflected in the whole procedure of sanding. In particular, the CAD model of the target object is automatically constructed with the structured-light technology, and the sanding behavior on the target surface is self-regulated under the desired impedance model. Such feature makes the robot capable of working towards uncertain objects with minimum human involvement. The proposed impedance controller has the model-free advantage, by using the adaptive neural networks (NNs) to compensate the uncertain dynamics and the unknown disturbances online. The stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results on different objects are presented to validate the performance of the developed robot. The implementation of the developed robot can systematically address the problems associated with manual works. Note to Practitioners—The current working environment of sanding is not healthy or safe to humans, due to the nature of noise, dust, high-speed sanding belt. By controlling the robot to autonomously perform sanding tasks can keep humans away from such environment and hence systematically address the issues of health and safety. This paper presents a new impedance control method for sanding robot. In impedance control, the control goal is specified as a dynamic relationship between the contact position and the interaction force. In this paper, the contact position is determined by using the 3D vision sensor, while the interaction force is regulated by referring to the human experience. In addition, the influence caused by unmodeled factors (e.g. unknown dynamics of the sanded object) is also dealt with by using the techniques of NNs. Such setting can effectively guarantee the sanding quality and also avoid the physical damage to the sanded object. Therefore, it lays the foundation for the autonomous robotic sanding.

In this paper, we investigate the consensus problem of multiple unmanned aerial vehicles (UAVs) in the presence of environmental constraints under a general communication topology containing a directed spanning tree. First, based on a position transformation function, we propose a novel dynamic reference position and yaw angle for each UAV to cope with both the asymmetric topology and the constraints. Then, the backstepping-like design methodology is presented to derive a local tracking controller for each UAV such that its position and yaw angle can converge to the reference ones. The proposed protocol is distributed in the sense that, the input update of each UAV dynamically relies only on local state information from its neighborhood set and the constraints, and it does not require any additional centralized information. It is demonstrated that under the proposed protocol, all UAVs reach consensus without violation of the environmental constraints. Finally, simulation and experimental results are provided to demonstrate the performance of the protocol.

This paper focuses on designing, modeling and validating a novel scalable multicopter whose deformation mechanism, called SNIAE-SSE, relies on a combination of simple non-intersecting angulated elements (SNIAEs) and straight scissor-like elements (SSEs). The proposed SNIAE-SSE mechanism has the advantages of single degree-of-freedom, fast actuation capability and large deformation ratio. In this work, enabled by the SNIAE-SSE mechanism, a quadcopter prototype with symmetrical and synchronous deformation is firstly developed, which facilitates a novel and controllably scalable multicopter system for us to analyze its modeling, as well as to validate its flight performance and dynamics during the deformation in several flight missions including hover, throwing, and morphing flying through a narrow window. Experimental results demonstrate that the developed scalable multicopter can maintain its stable flight behavior even both the folding and unfolding body deformations are fast performed, which indicates an excellent capability of the scalable multicopter to rapidly adapt to complex and dynamically changed environments.

In this paper, a simple tracking control scheme is proposed for quadrotor systems with uncertain dynamics. It precludes the necessity for prohibitive analytic computation of the derivatives of the desired (virtual) attitude that is typically employed in controlling quadrotor systems. Moreover, this control scheme is approximation-free in the sense that it does not incorporate any adaptive laws, observers, or command filters to compensate for unknown parameters in the dynamics and the absence of the analytic differentiation, thus exhibiting remarkably low complexity levels and making its implementation straightforward. The thrust saturation is approached in the position control design which also enables the singularity in desired attitude extraction to be avoided entirely. It is demonstrated that based on the proposed scheme, the tracking errors can be made arbitrarily small by appropriately selecting design parameters. Extensive simulations and experiments are performed to verify the effectiveness of our scheme.

Large demand for robotics and automation has been reflected in the sanding works, as current manual operations are labor-intensive, without consistent quality, and also subject to safety and health issues. While several machines have been developed to automate one or two steps in the sanding works, the autonomous capability of existing solutions is relatively low, and the human assistance or supervision is still heavily required in the calibration of target objects or the planning of robot motion and tasks. This paper presents the development of an autonomous sanding robot, which is able to perform the sanding works on an unknown object automatically, without any prior calibration or human intervention. The developed robot works as follows. First, the target object is scanned then modeled with the structured-light camera. Second, the robot motion is planned to cover all the surfaces of the object with an optimized transition sequence. Third, the robot is controlled to perform the sanding on the object under the desired impedance model. A prototype of the sanding robot is fabricated and its performance is validated in the task of sanding a batch of wooden boxes. With sufficient degrees of freedom (DOFs) and the customization of the end effector, the developed robot is able to provide a general solution to the autonomous sanding on many other different objects.

While the mechanism of Rope-Climbing provides much flexibility, it opens up challenges to the development of the controller for Robotic Manipulator installed on Rope-Climbing robot(RCR), which is called Rope-Climbing Robot Manipulator(RCRM) here. In particular, the deformable nature of the rope results in the vibration to the manipulator and hence affects the positioning of the end effector. In this paper, a new adaptive vision-based controller is proposed for RCRM, which enables the robot to carry out the high-accuracy task under the unknown vibration from the rope. The proposed controller guarantees the performance of the robot in twofold. First, the control problem is directly formulated in the image space such that the exact spatial relationship between the moving base of the manipulator (due to the vibrating rope) and the target (e.g. the wall) is not required. Second, novel adaptation laws are developed to estimate the vibration from the rope online and are cancelled out in the robot control input to stabilize the end effector. The stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results are presented to illustrate the performance of the proposed controller.

The ability of rope-climbing robots in aloft operation is limited by its self-supporting and locomotion ability. In many applications, a given task is also too complex to be achieved by a single rope-climbing robot acting alone. The solution of multiple rope-climbing robots can overcome the limitations. However, existing control methods for rope-climbing robots are limited to single robot, and the open issue of coordination between multiple rope-climbing robots has not been systematically addressed. This paper presents a new synchronization scheme for position control of multiple rope-climbing robots, such that each robot moves to the corresponding desired position while synchronizing the heights between each other. Maintaining the same height is very important to guarantee the stability of the task-oriented manipulator installed among multiple robots, when it is performing the manipulation task. The development of the proposed controller is based on the singular perturbation approach, by treating the fast actuator dynamics as a perturbation of the slow robot dynamics, such that the lowest control complexity is achieved. The exponential stability of the overall system that consists of the fast and slow subsystems is proved by using Tikhonov’ s theorem. Experimental results are presented to illustrate the performance of the proposed controller.

In this paper, we present a new feedback method to automatically servo-control the 3-D shape of soft objects with robotic manipulators. The soft object manipulation problem has recently received a great deal of attention from robotics researchers because of its potential applications in, e.g., food industry, home robots, medical robotics, and manufacturing. A major complication to automatically control the shape of an object is the estimation of its deformation properties, which determines how the manipulator's motion actively transforms into deformations. Note that these properties are rarely known beforehand, and its offline parametric identification is difficult and/or impractical to conduct in many applications. To cope with this issue, we developed a new algorithm that computes in real time the unknown deformation parameters of a soft object; this algorithm provides a valuable adaptive behavior to the deformation controller, something we cannot achieve with traditional fixed-model approaches. In contrast with most controllers in the literature, our new method can explicitly servo-control 3-D deformations (and not just 2-D image projections) in an entirely model-free way. To validate the proposed adaptive controller, we present a detailed experimental study with robotic manipulators.

In this paper, we propose a novel design of compliant safe joint, which has flexibility when the work load exceeds a predefined threshold. The compliance is generated by a spring. We design a special transmission mechanism to convert axial motion into circumferential motion such that the linear compliance can be converted into circular one. When the end-effector of a surgical robot actuated by the compliant safe joints collides with patient's body, the compliance of the joints will protect the patient by absorbing part of the collision energy. Because of the system's special mechanical structure, the control methods should be different when it works under different states. We propose a simple algorithm to choose control methods so that the system can work both under rigid and flexible states with different controllers. We have built a prototype to validate the design and the controller.

This paper presents the development of an endoscope manipulator with passive and active structures for functional endoscopic sinus surgery (FESS). The 5-DoF passive structure has three translations and two rotations (T3R2) that allows the surgeon to manually place the endoscope near to the entry point during. The 4-DoF motorized structure (T2R2) actively controls the endoscope's position based on the surgeon's input commands. We analyze the reciprocal screw of the passive and active structures. The motion control system is based on a real-time Linux kernel that processes the commands from the surgeon and controls the manipulator's active joints. A user control interface based on an IMU fastened on the surgeon's foot is developed; this interface measures the foot's posture and through a series of gestures, it provides the desired pan/tilt/zoom motions of the camera. The developed endoscope manipulator allows the surgeon to conduct ‘two-hand’ operations while retaining direct control of the camera. We present an experimental study to validate the performance of the robotic prototype.

In this paper, we address the positioning problem of remote centre of motion (RCM) mechanisms with uncalibrated image feedback from a monocular camera. Nowadays, RCM mechanisms are widely used in minimally invasive robotic surgery due to their ability to distally rotate a tool around a fixed entry port; note that in most surgical applications, the tools are typically controlled by manual/teleoperated motion commands given by a human user. In this paper, we depart from the traditional manual control scheme and derive sensor-based methods to automatically position the manipulated tool using real-time image feedback. To this end, we first characterise the mechanism's 3-DOF configuration with the angle of the image projected tool and scalar distances between feature points. To cope with uncertainty in the camera's calibration parameters, we propose two gradient descent estimators that adaptively compute the unknown Jacobian matrix; the stability of these algorithms is proved with Lyapunov theory. Finally, we derive a kinematic image-based controller and evaluate its performance with several positioning experiments.

In this paper, we present a new robotic uterine positioner for total laparoscopic hysterectomy. The robot is designed to actively position the patient's uterus during surgery, a lengthy and tedious task that is traditionally performed by a human assistant. Safety is simply the most important concern when developing robots for surgical purposes; we address this concern in the design of our robot from a mechanical perspective. To this end, we develop a 3-DOF robotic uterine positioner with an in-body remote center of motion (RCM); this key feature allows to prevent injuries to the patient when large motions occur at the cervix. A linearly-actuated arc-guided RCM mechanism is introduced to guarantee the rigidity and stability of the robot; The system's design allows to manipulate the uterus in a decoupled manner, thus control complexity can be reduced. Passive safety mechanisms are also implemented in all DOF of the robot in order to limit the interaction forces with the patient. Experiments, including an ex-vivo test conducted with cadaver, are conducted to verify the robot's performance.

Despite the recent progress in physically interactive and surgical robotics, the active deformation of compliant objects remains an open problem. The main obstacle comes from the difficulty to identify/estimate the object's deformation properties. This paper presents a new visually servoed deformation controller for unknown elastic objects. The control law is designed using the passivity-based framework. The proposed method exploits visual feedback to iteratively estimate the deformation Jacobian matrix, avoiding any identification steps. We prove that even in the presence of inexact estimations, the controller ensures input-to-state stability (i.e. dissipativity) with respect to time-varying disturbances. Finally, an experimental study with several deformation tasks is presented to validate the theory.

Despite the recent progress in physically interactive and surgical robotics, the active deformation of compliant objects remains an open problem. The main obstacle to its implementation comes from the difficulty to identify or estimate the object's deformation model. In this paper, we propose a novel vision-based deformation controller for robot manipulators interacting with unknown elastic objects. We derive a new dynamic-state feedback velocity control law using the passivity-based framework. Our method exploits visual feedback to estimate the deformation Jacobian matrix in real time, avoiding any model identification steps. We prove that even in the presence of inexact estimations, the closed-loop dynamical system ensures input-to-state stability (i.e., full dissipativity) with respect to external disturbances. An experimental study with several deformation tasks is presented to validate the theory.

In this paper, we analyse and present a control approach using the energy shaping formulation to explicitly regulate the applied force of a robot manipulator in contact with a purely elastic environment. The potential energy of the robot-environment system is shaped in a way that its local equilibrium implies the application of the desired force onto the contact surface. This potential shaping is realised based on the available contact force feedback. Also, it is shown how force feedback can be employed to modulate the amount of energy externally injected by a source subsystem, and with this achieve exact force convergence. Experimental results are presented to validate this approach.

This paper presents a self-rescue mechanism for a screw drive in-pipe robot, which only uses one DC motor. The robot has two working modes, Normal Working Mode and Self-rescue Mode. Under normal working mode, the robot propels itself in the pipe just as other classical screw drive robots. When the robot encounters the obstacle and gets jammed, the lock up mechanism and motion control mechanism of the robot are activated. Then, the robot changes from working mode to self-rescue mode and moves away in the reverse direction to avoid jamming in the pipe. The change of the working mode is determined by the characteristics of the mechanism. The proposed mechanism can be used as a safety protection method for the pipe robot. Experiments have been conducted to testify the proposed mechanism. Compared with those with screw drive mechanisms, robots with self-rescue mechanism are able to avoid jamming in the pipe.

In this paper, a mobile mechanism with driving capability and detecting function is proposed for in-pipe inspection task. Based on this mechanism, a robot is designed and fabricated. The advantage of this robot is that it has mobile ability in the pipe and detecting function for inspection, while only one DC motor is installed. This results in low energy consumption and low cost to make. The robot propels itself in the pipe under a driving mode, and it is used for finding the defect of the pipe under a detecting mode. By switching these two working modes, the robot performs the inspection task without other extra DC motors. Moreover, a velocity change mechanism is introduced to adapt the change of the payload through adjusting the incline angle of the roller. The characteristics of this mechanism are analyzed by comparison with a classical screw drive robot and a direct drive robot. Finally, basic experiments are conducted to testify the mobility and efficiency of this robot.

A robot, which is composed of adaptive mobile mechanism, is developed for the purpose of performing the internal inspection tasks of pipelines. Adaptability and efficiency are the basic considerations for this robot. Based on these concepts, a prototype is designed and fabricated. The proposed adaptive mobile mechanism equipped with one actuator can perform two working modes, a normal working mode and an assistant enhanced mode. Robot under the normal working mode is used for moving in pipe or monitoring the inner surface of the pipe. On the other hand, robot under the assistant enhanced mode will produce a larger torque to help itself surmount an obstacle in the pipe without any other driving actuator. This special feature is achieved by applying a power transmission mechanism. The rotation problem of the stator is solved according to the calculation results of the robot kinematics. Basic experiments have been conducted to testify the adaptability and efficiency of the robot.