As researchers have pushed the limits of what can be accomplished by a single robot operating in a known or unknown environment, a greater emphasis has been placed on the utilization of mobile multi-robotic systems to accomplish various objectives. In transitioning from a robot-centric approach to a system-centric approach, considerations must be made for the computational and communicative aspects of the group as a whole, in addition to electromechanical considerations of individual robots. This paper reviews the state-of-the-art of mobile multi-robotic system research, with an emphasis on the confluence of mapping, localization and motion control of robotic system. Methods that compose these three topics are presented, including areas of overlap, such as integrated exploration and simultaneous localization and mapping. From these methods, an analysis of benefits, challenges and tradeoffs associated with multi-robotic system design and use are presented. Finally, specific applications of multi-robotic systems are also addressed in various contexts.

Experiments with a nonlinear trajectory-tracking controller for marine unmanned surface vessels are reported. The tracking controller is designed using a nonlinear robust model-based sliding mode approach. The marine vehicles can track arbitrary desired trajectories that are defined in Cartesian coordinate as continuous functions of time. The planar dynamic model used for the controller design consists of 3 degrees of freedom (DOFs) of surge, sway, and yaw. The vessel only has two actuators, so the vessel is underactuated. Therefore, only two outputs, which are functions of the 3-DOF, can be controlled. The Cartesian position of a control point on the vessel is defined as the output. The orientation dynamics is not directly controlled. It has been previously shown that the orientation dynamics, as the internal dynamics of this underactuated system, is stable. The result of field experiments show the effectiveness of tracking control laws in the presence of parameter uncertainty and disturbance. The experiments were performed in a large outdoor pond using a small test boat. This paper reports the first theoretical development and experimental verification of the proposed model-based nonlinear trajectory-tracking controller.

Hazardous terrains pose a crucial challenge to mobile robots. To operate safely and efficiently, it is necessary to detect the terrain type and modify operation strategies in real-time. Fast analytical models of wheeled locomotion on deformable terrains are thus important. Based on classic terramechanics, a closed-form wheel–soil interaction model was derived by quadratic approximation of stresses along the wheel–soil interface. The bulldozing resistance and the effects of grousers were also added for more accurate prediction of wheel contact forces. A non-iterative method was proposed to estimate the entry angle, by using approximated vertical pressure acting on the wheels. The computational efficiency was improved by avoiding traditional recursive search. Real-time computation of the wheel contact forces is achieved by the terramechanics-based formula (TBF), which was developed by integrating the wheel–soil interaction model and the entry angle estimator. In addition, an automotive-inspired approach was used to integrate the TBF and the simplified vehicle dynamics model for fast simulation of mobile robots. Stability problems in numerical simulation could be avoided by this method. The above models were verified by comparing simulation results and experiment data, including single-wheel experiments and full-vehicle experiments.

This paper delivers a proof of a statement due to Ge and Lee. Specifically, these authors stated, without proof, that the entries of the inertia matrix may be completely parameterized by stacking elements of a regressor superset. This superset has the advantage of avoiding to derive the complete dynamics of a robot manipulator. On the basis of both mechanics and combinatorial arguments, we deliver a formal proof. In addition, we improve the estimations by sorting joint variables and partitioning the inertia matrix that results into the reduction of the regressor superset. The number of nonlinear functions in the regressor is also quantified. A 2 degrees of freedom revolute robot is presented to illustrate these ideas.

This paper presents applications of group theory tools to simplify the analysis of kinematic chains associated with mechanisms and parallel manipulators. For the purpose of this analysis, a kinematic chain is described by its properties, i.e. degrees-of-control, connectivity and redundancy matrices. In number synthesis, kinematic chains are represented by graphs, and thus the symmetry of a kinematic chain is the same as the symmetry of its graph. We present a formal definition of symmetry in kinematic chains based on the automorphism group of its associated graph. The symmetry group of the graph is associated with the graph symmetry. By using the group structure induced by the symmetry of the kinematic chain, we prove that degrees-of-control, connectivity and redundancy are invariants by the action of the automorphism group of the graph. Consequently, it is shown that it is possible to reduce the size of these matrices and thus reduce the complexity of the kinematic analysis of mechanisms and parallel manipulators in early stages of mechanisms design.

This paper investigates algorithms for enabling surgical slave robots to autonomously explore shape and stiffness of surgical fields. The paper addresses methods for estimating shape and impedance parameters of tissue and methods for autonomously exploring perceived impedance during tool interaction inside a tissue cleft. A hybrid force-motion controller and a cycloidal motion path are proposed to address shape exploration. An adaptive exploration algorithm for segmentation of surface features and a predictor-corrector algorithm for exploration of deep features are introduced based on discrete impedance estimates. These estimates are derived from localized excitation of tissue coupled with simultaneous force measurements. Shape estimation is validated in ex-vivo bovine tissue and attains surface estimation errors of less than 2.5 mm with force sensing resolutions achievable with current technologies in minimally invasive surgical robots. The effect of scan patterns on the accuracy of the shape estimate is demonstrated by comparing the shape estimate of a Cartesian raster scan with overlapping cycloid scan pattern. It is shown that the latter pattern filters the shape estimation bias due to frictional drag forces. Surface impedance exploration is validated to successfully segment compliant environments on flexible inorganic models. Simulations and experiments show that the adaptive search algorithm reduces overall time requirements relative to the complexity of the underlying structures. Finally, autonomous exploration of deep features is demonstrated in an inorganic model and ex-vivo bovine tissue. It is shown that estimates of least constraint based on singular value decomposition of locally estimated tissue stiffness can generate motion to accurately follow a tissue cleft with a predictor-corrector algorithm employing alternating steps of position and admittance control. We believe that these results demonstrate the potential of these algorithms for enabling “smart” surgical devices capable of autonomous execution of intraoperative surgical plans.

This paper introduces the design, analysis, and experimental results of a fast mesoscale (12 cm length) quadruped mobile robot that employs unconventional actuators. Four legs of the robot are actuated by two pieces of piezocomposite actuator named LIPCA, which enables the robot to achieve the bounding gait with only one degree of freedom per leg. The forward locomotion is obtained by a creative idea in the design and the speed can be controlled by changing the frequency of actuators. The mechanism of power transfer has been improved in order to use the actuation power more efficiently. Two small RC-servo motors are added to control the locomotion direction. In addition, a small power supply and control circuit is developed that is fit for the robot. Our experiments show that the robot can locomote as fast as about two times its body length per second with the circuit board and a battery installed. The robot is also able to change the heading direction in a controlled way and is capable of continuous operation for 35 min.

This paper presents a novel line of sight control system for a robot vision tracking system, which uses a position feedforward controller to preposition a camera, and a vision feedback controller to compensate for the positioning error. Continuous target tracking is an important function for service robots, surveillance robots, and cooperating robot systems. However, it is difficult to track a specific target using only vision information, while a robot is in motion. This is especially true when a robot is moving fast or rotating fast. The proposed system controls the camera line of sight, using a feedforward controller based on estimated robot position and motion information. Specifically, the camera is rotated in the direction opposite to the motion of the robot. To implement the system, a disturbance compensator is developed to determine the current position of the robot, even when the robot wheels slip. The disturbance compensator is comprised of two extended Kalman filters (EKFs) and a slip detector. The inputs of the disturbance compensator are data from an accelerometer, a gyroscope, and two wheel-encoders. The vision feedback information, which is the targeting error, is used as the measurement update for the two EKFs. Using output of the disturbance compensator, an actuation module pans the camera to locate a target at the center of an image plane. This line of sight control methodology improves the recognition performance of the vision tracking system, by keeping a target image at the center of an image frame. The proposed system is implemented on a two-wheeled robot. Experiments are performed for various robot motion scenarios in dynamic situations to evaluate the tracking and recognition performance. Experimental results showed the proposed system achieves high tracking and recognition performances with a small targeting error.

This paper presents new proofs of four stability properties (semiglobal strict passivity, semiglobal asymptotic stability, semiglobal input-to-state stability, and semiglobal uniform ultimate boundedness with an arbitrarily reducible ultimate bound) of a rigid-link manipulator under proportional-integral-derivative (PID) position control. The proofs employ a strict Lyapunov function and a novel parameterization to provide four inequality conditions for the stability properties. In those inequalities, arithmetic operations on physical quantities are physically consistent if the joints are all revolute or all prismatic. A gain selection procedure is presented by which the ultimate bounds of velocity error, position error, and its integral can be independently designed.

In this paper, for a special class of the Stewart parallel mechanism, whose moving platform and base one are two dissimilar semi-symmetrical hexagons, the position-singularity of the mechanism for a constant-orientation is analyzed systematically. The force Jacobian matrix [J]T is constructed based on the principle of static equilibrium and the screw theory. After expanding the determinant of the simplified matrix [D], whose rank is the same as the rank of the matrix [J]T, a cubic symbolic expression that represents the 3D position-singularity locus of the mechanism for a constant-orientation is derived and graphically represented. Further research shows that the 3D position-singularity surface is extremely complicated, and the geometric characteristics of the position-singularity locus lying in a general oblique plane are very difficult to be identified. However, the position-singularity locus lying in the series of characteristic planes, where the moving platform coincides, are all quadratic curves compromised of infinite many sets of hyperbolas, four pairs of intersecting lines and a parabola. For some special orientations, the quadratic curve can degenerate into two lines or even one line, all of which are parallel to the ridgeline. Two theorems are presented and proved for the first time when the geometric characteristics of the position-singularity curves in the characteristic plane are analyzed. Moreover, the kinematic property of the position-singularity curves is obtained using the Grassmann line geometry and the screw theory. The theoretical results are demonstrated with several numeric examples.

Parallel kinematics machines (PKMs) can exhibit kinematics as well as actuation redundancy. While the meaning of kinematic redundancy has been already clarified for serial manipulators, actuation redundancy, which is only possible in PKMs, is differently classified in the literature. In this paper a consistent terminology for general redundant PKM is proposed. A kinematic model is introduced with the configuration space (c-space) as central part. The notion of kinematic redundancy is recalled for PKM. C-space, output, and input singularities are distinguished. The significance of the c-space geometry is emphasized, and it is pointed out geometrically that input singularities can be avoided by redundant actuation schemes. In order to distinguish different actuation schemes of PKM, a nonlinear control system is introduced whose dynamics evolves on c-space. The degree of actuation (DOA) is introduced as the number of independent control vector fields, and PKMs are classified as full-actuated and underactuated machines. Relating this DOA to degree of freedom allows to classify the actuation redundancy.

Among the many challenges to deal with, when a robot is interacting with its environment, friction at the contact surface and/or at the joints is one of the most important to be considered. In this paper we propose a control algorithm for the tracking of position and force (unconstrained orientation case only) of a manipulator end-effector that does not require the robot model for implementation. This characteristic has the advantage of making it capable to compensate friction effects without any previous estimation. Furthermore, no velocity measurements are needed, and the unit quaternion is employed for orientation control. Experimental and simulation results are provided.