This paper presents a new observer-based adaptive controller for handling an object with unknown geometry, center of mass, and inertia using a cooperative robotic system. The cooperative robotic system comprises three Cartesian robots, where robots and the grasped object form a closed-loop kinematic chain. The unknown object is approximated by three virtual links of unknown lengths rigidly attached to one another at the object's center of mass (COM). Due to the unknown COM and unknown inertia of the object, the lengths and inertia of these virtual links are unknown, resulting in kinematic and dynamic uncertainties in the control system. A parameter estimator is proposed to estimate the object's COM to compensate for kinematic uncertainties of the system. Moreover, a new dynamic adaptation law is developed to cope with dynamic uncertainties of the object. The dynamic equations of the cooperative system are transformed from joint space into task space. These task space dynamics are transformed into object space by passively decomposing the dynamics into two decoupled systems, i.e. locked and shaped systems. An adaptive controller is developed for the locked system, and the shaped system is controlled by a composite controller based on a PD controller plus a stabilizing damping term. The stability of the proposed controllers is shown using the passivity concept and Lyapunov theorem. Simulation results show that the closed-loop position error asymptotically converges to zero. It is also shown that kinematic and dynamic adaptation parameters converge to real and bounded values respectively.

Control of rigid–flexible multi-body systems in space, during cooperative manipulation tasks, is studied in this paper. During such tasks, flexible members such as solar panels may vibrate. These vibrations in turn can lead to oscillatory disturbing forces on other subsystems, and consequently may produce significant errors in the position of operating end-effectors of cooperative arms. Therefore, to design and implement efficient model-based controllers for such complicated nonlinear systems, deriving an accurate dynamics model is required. On the other hand, due to practical limitations and real-time implementation, such models should demand fairly low computational complexity. In this paper, a precise dynamics model is derived by virtually partitioning the system into two rigid and flexible portions. These two portions will be assembled together to generate a proper model for controller design. Then, an adaptive hybrid suppression control (AHSC) algorithm is developed based on an appropriate variation rule of a virtual damping parameter. Finally, as a practical case study a space free-flying robot (SFFR) with flexible appendages is considered to move an object along a desired path through accurate force exertion by several cooperative end-effectors. This system includes a main rigid body equipped with thrusters, two solar panels, and two cooperative manipulators. The system also includes a third and fourth arm that act as a communication antenna and a photo capturing camera, respectively. The maneuver is deliberately planned such that flexible modes of solar panels get stimulated due to arms motion, while obtained results reveal the merits of proposed controller as will be discussed.

The study of arm muscles for independent operations leading to prosthetic design was carried out. Feature extraction was done on the recorded signal for investigating the voluntary muscular contraction relationship for different arm motions and then repeated factorial analysis of variance (ANOVA) technique was implemented to analyze effectiveness of signal. The electronic design consisted of analog and digital signal processing and controlling circuit and mechanical assembly consisted of wrist, palm and the fingers to grip the object in addition to a screw arrangement connected to a low power DC motor and gear assembly to open or close the hand. The wrist is mechanically rotated to orient the hand in a direction suitable to pick up/hold the object. The entire set up is placed in a casing which provides a cosmetic appeal to the artificial hand and the connected arm. The design criteria include electronic control, reliability, light weight, variable grip force with ease of attachment for simple operations like opening, grasping and lifting objects of different weight with grip force slightly more than enough just like that of a natural hand.

In this paper, we propose and examine a force-resisting balance control strategy for a walking biped robot under the application of a sudden unknown, continuous force. We assume that the external force is acting on the pelvis of a walking biped robot and that the external force in the z-direction is negligible compared to the external forces in the x- and y-directions. The main control strategy involves moving the zero moment point (ZMP) of the walking robot to the center of the robot's sole resisting the externally applied force. This strategy is divided into three steps. The first step is to detect an abnormal situation in which an unknown continuous force is applied by examining the position of the ZMP. The second step is to move the ZMP of the robot to the center of the sole resisting the external force. The third step is to have the biped robot convert from single support phase (SSP) to double support phase (DSP) for an increased force-resisting capability. Computer simulations and experiments of the proposed methods are performed to benchmark the suggested control strategy.

Autonomous docking is a focus of research in the field of self-assembly robots. Navigation is a significant stage in the process of autonomous docking between two robotic modules; it determines the efficiency of docking and even the success and failure of the docking task. In most cases, it is too difficult to simultaneously satisfy both linear and angular displacement constraints in a single dynamic numerical computation process. In the present paper, the navigation process is divided into two stages: first, the angular displacement constraint is satisfied, and then the linear displacement condition is fulfilled. In this way, the constraints are loosened and the difficulty of numerical computation is thereby effectively reduced. This two-stage docking navigation model is the main contribution of the present work. By taking the non-holonomic nature of the navigation behavior into consideration, both kinematic and dynamic analyses are performed, and the voltage data of the DC motors required by the two-stage docking navigation are obtained. Finally, docking navigation experiments are completed on a self-assembly modular robot named Sambot. It is verified that the present two-stage strategy is effective in controlling the docking navigation process.

This paper develops a new adaptive actuator failure compensation algorithm for the control of a cooperative robotic system subject to uncertain actuator failures. The benchmark robotic system has two manipulators to balance a rigid platform, and the right-side manipulator contains one actuator and the left-side manipulator has two actuators (one of which may fail during system operation, but it is uncertain how much, when and which actuator may fail). The developed adaptive actuator failure compensation scheme, based on adaptive integration of three individual failure compensators and direct adaptation of controller parameters, is capable of ensuring desired closed-loop stability and asymptotic output tracking, despite the failure uncertainties. Such an adaptive actuator failure compensation method is extended to control of a general cooperative robotic system. Simulation results are shown to verify the desired adaptive failure compensation control performance.

This paper proposes a modular caterpillar climbing robot using spines as the attaching tools. To improve the reliability of the spines' engagement and disengagement, this paper discusses the reasonable trajectory of the spine and designs a driving mechanism of the spine based on the compliant mechanism theory. Then some compliant modules are designed and realized to build the caterpillar climbing robot. A climbing gait is designed to avoid collisions between the spines and the wall, and allows the robot to climb on a stucco-like wall with a 72○ incline. The real tests reveal that the deformation of the compliant toes reduces the sliding forces between the spines and the wall, and improve the climbing action obviously.

A continuum manipulator, such as a multisection trunk/tentacle robot, performs manipulation tasks by continuously deforming into different concave shapes. While such a robot is promising for manipulating a wide range of objects in less-structured and cluttered environments, it poses a greater challenge to collision detection than conventional, articulated manipulators. Existing collision detection algorithms are built upon intersection checking between convex primitives, such as between two convex polygons or polyhedra, with the assumption that both the manipulator and the objects in the environment are modeled in terms of those primitives, for example, as polygonal meshes. However, to approximate a continuum manipulator with a polygonal mesh requires a fine mesh because of its concavity, and each time the manipulator changes its configuration by deforming its shape, the mesh has to be updated for the new configuration. This makes mesh-based collision detection involving such a robot much more computationally expensive than that involving an articulated manipulator with rigid links.

Hence, we introduce an efficient algorithm for Collision Detection between a Continuum Manipulator (CD-CoM) and its environment based on analytical intersection checking with nonconvex primitives. Our algorithm applies to the exact model of any continuum manipulator consisting of multiple uniform-curvature sections of toroidal and (sometimes) cylindrical shapes as well as more general continuum manipulators whose sections can be approximated by toroidal and cylindrical primitives. Our test results show that using this algorithm is both more accurate and efficient in time and space to detect collisions than approximating a continuum manipulator as a polygonal mesh. Moreover, the CD-CoM algorithm also provides the minimum distance information between the continuum manipulator and objects when there is no collision. Such an efficient algorithm is essential for path/trajectory planning of continuum manipulators in real-time.

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach.

This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach.

This paper presents what is termed as the supervoxel normal distributions transform (SV-NDT), a novel three-dimensional (3-D) registration algorithm which improves the performance of the three-dimensional normal distributions transform (3-D NDT) significantly. The 3-D NDT partitions a model scan using a 3-D regular grid. Generating normal distributions using the 3-D regular grid causes considerable information loss because the 3-D regular grid does not use any information pertaining to the local surface structures of the model scan. The best type of surface (the constituent unit of each scan) for modeling with one normal distribution is known to be the plane. The SV-NDT reduces the loss of information using a supervoxel-generating algorithm at the partitioning stage. In addition, it uses the information of the local surface structures from the data scan by replacing the Euclidean distance with a function that uses local geometries as well as the Euclidean distance when each point in the data scan is matched to the corresponding normal distribution. Experiments demonstrate that the use of the supervoxel-generating algorithm increases the modeling accuracy of the normal distributions and that the proposed 3-D registration algorithm outperforms the 3-D NDT and other widely used 3-D registration algorithms in terms of robustness and speed on both synthetic and real-world datasets. Additionally, the effect of changing the function to create correspondences is also verified.

Robots running on water have attracted the attention of researchers in the last decades as an alternative to conventional aquatic propulsion mechanisms. Up to now, a large scale robot capable of running on water has not been realized. Bouncing on water is a prerequisite for running on water. For this reason, the development of a water bouncing robot represents a necessary first step. The paper presents the model of a 2-degree-of-freedom water bouncing robot inspired by the pogo-stick, a device for jumping off the ground in a standing position. An analytical model of the impact force between “robot's foot” and water is provided for both water-entry and water-exit phases. Such a model has been integrated in a dynamic simulation of whole robot. The model represents a useful and general framework to gain an insight into the parameters that characterize the efficiency of robot.