Laparoscopic and Single Port Access Surgery (SPAS) present unique dexterity challenges related to dual-arm operations in confined spaces and tele-manipulation of highly dexterous surgical slaves. In an effort to reduce tele-manipulation burden, new paradigms for semi-automating surgical tasks are needed. This paper presents a new minimal constraint suturing and automated choice of handedness for anthropomorphic dual-arm robots. The automated choice of handedness supports surgeons during tele-manipulation of complex robotic slaves where dexterity and workspace constraints are difficult to learn. This criterion is also used to support automated dual-arm rendezvous for quicker suture exchange during dual-arm suturing. The minimal constraint algorithm presented in this paper allows surgeons to operate within a shared-control tele-manipulation framework whereby the surgeon controls the needle insertion speed and the robot controls the needle orientation while respecting a minimalistic set of tissue constraints. This framework is evaluated on a novel insertable robotic end-effectors platform for SPAS. A simulation study demonstrates the effectiveness of the automated choice of handedness criterion through a study of dexterity limitations of each arm. Additional simulations show the proposed algorithm for automated rendezvous and suture exchange.

Employing passive dynamics of the simplest point-foot walker, we have shown that the walking surface could have a great role in promoting the gait stability. In this regard, the stabilization of the simplest walking model,3 between the range of slopes greater than 0.0151 rad. and less than 0.26 rad., has been achieved. The walker like other passive dynamic walking models has no open or closed-loop control system; so, is only actuated by the gravity field. Moreover, no damper or spring is used. Obviously, according to the model's unstable behavior, it is unable to walk on an even flat ramp between the mentioned intervals.3 Here, instead of restraining the model, we let it explore other smooth surfaces, walking on which, will end in an equally inclined surface. To reach the objective, we employ a parallel series of fixed straight lines (local slopes) passing through contact points of an unstable cycling gait, which is generated by an ordinary ramp. To categorize, we have nicknamed those local slopes that guide the biped to a stable cyclic walking, “Ground Attractors,” and the other, leading it to a fall, “Repulsive Directions.” Our results reveal that for the slope <0.26 rad., a closed interval of ground attractors could be found. Stabilization of those unstable limit cycles by this technique makes obvious the key role of walking surface on bipedal gait. Furthermore, following our previous work,13 the results confirm that the two thoroughly similar walking trajectories can have different stability. All of these results strongly demonstrate that without considering the effects of a walking surface, we cannot establish any explicit relationship between the walker's speed and its stability.

Slotine and Li's modification is a well-known, simple, and elegant approach for robot adaptive control to avoid the feedback of joint accelerations. This paper presents a simple strategy to implement a regressor-free adaptive impedance controller without using Slotine and Li's modification. In the new strategy, the joint acceleration vector and the dynamics of robot are assumed to be unavailable. Their effects are covered by using the function approximation technique so that there is no need for the joint acceleration feedback. The closed-loop stability and boundedness of internal signals are justified by the Lyapunov-like technique. Experimental results for a two-dimensional (2D) robot are presented to show the effectiveness of the proposed strategy.

This paper presents a novel scheme for achieving attitude control of a tumbling combination system in the post-capture phase of a tethered space robot (TSR). Given the combination rotation characteristics, tether force is applied to provide greater control torques for stabilising the attitude. The proposed control scheme involves two attitude controllers, which coordinate the controller of the tether force and thruster force and the controller of single thruster force. The numerical simulations include a comparison between this coordinated control and the traditional thruster control and a sensitivity analysis on initial values of parameters. Simulation results validate the feasibility of the attitude control scheme for a tumbling combination system, and fuel consumption of the attitude control is efficiently reduced using the coordinated control strategies.

Mechanical regulator-free bicycle robots have lighter weight and fewer actuators than the traditional regulator-based bicycle robots. In order to deal with the difficulty of maintaining balance for this kind of bicycle robot, we consider a front-wheel drive and mechanical regulator-free bicycle robot. We present the methodologies for realizing the robot's ultra-low-speed track-stand motion, moderate-speed circular motion and high-speed rectilinear motion. A simplified dynamics of the robot is developed using three independent velocities. From the dynamics, we suggest there may be an underactuated rolling angle in the system. Our balancing strategies are inspired by human riders' experience, and our control rules are based on the bicycle system's underactuated dynamics. In the case of track-stand and circular motion, we linearize the frame's rolling angle and configure the robot to maintain balance by the front-wheel's motion with a fixed front-bar turning angle. In the case of the rectilinear motion, we linearize both front-bar steering angle and front-wheel rotating angle, and configure the system to maintain balance by the front-bar's turning with a constant front-wheel rotating rate. Numerical simulations and physical experiments are given together to validate the effectiveness of our control strategies in realizing the robot's proposed three motions.

Studying wheel and ground interaction during motion has the potential to increase the performance of localization, navigation, and trajectory tracking control of a mobile robot. In this paper, a differential mobile robot is modeled in a way that (traction, rolling, and lateral) wheel forces are included in the overall system dynamics. Lateral wheel forces are included in the mathematical model together with traction and rolling forces. A least square parameter estimation process is proposed to estimate the parameters of the wheel forces. In order to implement the proposed methodologies, an experimental setup is used. The setup contains a differentially driven mobile robot, a specially constructed test surface, and a camera system attached at the top of surface for obtaining ground truth. Models having one or more wheel forces are simulated to find the most realistic model. Simulation results are verified by experiments.

This paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. A novel image processing procedure is developed to estimate the distance between the robot and obstacles based-on inverse perspective transformation (IPT) in an image plane. A robust image processing solution is proposed to detect and segment a drivable ground area within the camera view. The proposed method integrates robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view. After IPT and ground region segmentation, distance measurement results are obtained similar to those of a laser range finder for mobile robot obstacle avoidance and navigation. The merit of this algorithm is that the mobile robot can have the capacity of path finding and obstacle avoidance by using a single monocular camera. Practical experimental results on a wheeled mobile robot show that the proposed imaging system successfully obtains distances of surrounding objects for reactive navigation in an indoor environment.

Controlling a walking biped robot is a challenging problem due to the robot's complex and uncertain dynamics. In order to tackle this problem, we propose a sliding mode controller based on a dynamic model that we obtained using the conformal geometric algebra (CGA) approach. An important contribution of this paper is the development of algorithms using the CGA framework. The CGA framework permits us to use lines, points, and other geometric entities to obtain the Lagrange equations of the system. The references for the joints of the robot were obtained in a bio-inspired way following the kinematics of a walking human body. The first and second derivatives of the reference signal were obtained via an exact robust differentiator based on a high-order sliding mode. We analyzed the performance of the proposed control schemes by using bio-inspired walking patterns and simulations.

A redundantly actuated parallel kinematic machine (PKM) can be used to avoid singularities, normalize manipulability, and increase the stiffness of anon-redundant mechanism. In this study, a redundantly actuated symmetrical PKM with five revolute (5R) joints is optimized for isotropic stiffness in the workspace. The stiffness of the 5R symmetrical PKM is calculated by the superposition of the actuator stiffness and the structural stiffness. We compared the stiffness of anon-redundant PKM and a redundant PKM. Compliance ellipses of the actuator stiffness and the structural stiffness of the non-redundant PKM resulted in the same configurations in the workspace, while those of the redundant PKM resulted in very different configurations. Optimization was performed by determining the optimal actuator torques that are needed to maximize the conditioning index. Optimal results considering structural stiffness can provide a more uniform directional stiffness than optimal results considering the index. When the strength of the linkages in a PKM is weak, the structural stiffness affects the actual stiffness considerably. We believe that the results of this study can be used to help design and control redundant PKMs.

This paper presents a novel method to determine the workspace of parallel manipulators using a variant of the Firefly Algorithm, which is one of the emerging techniques in swarm artificial intelligence. The workspace is defined as a set of all the coordinates in the search space that are accessible by the parallel manipulator end effector. The workspace formulation of the parallel manipulator considered in this paper has actuated and passive joint displacements which values are limited by their physical constraints. A special fitness function that discriminates between accessible and inaccessible coordinates is formulated based on the joint limitations. By finding these coordinates using the proposed Firefly Algorithm, the workspace of the manipulator can be constructed. The proposed method is an easy-to-implement alternative solution to the current numerical methods for workspace determination. The method consists of two stages of operation. The first stage maps the workspace to find the initial results with a space filling approach, in which a number of coordinates in the workspace are identified. The second stage refines the results with a boundary detection approach which focuses on the mapping of the boundaries of the workspace. The method is illustrated by its application to determine the 2D, 3D, and 6D workspaces of a Gough--Stewart Platform manipulator. Furthermore, the method is compared with a more rigorous interval analysis method in terms of computational cost and accuracy.

Pipeline grids of various size and material are pervasive in today's modern society. The frequent inspection and maintenance of such pipeline grids have presented a tremendous challenge. It is advocated that only advanced robot design embedded with intelligent electronics and control algorithms could perform the job. Given the ever increasing demands for intelligent in-pipe robots, various in-pipe drive mechanisms have been reported. One of the simplest is helical wheel drives that have only one degree of freedom. All previously reported in-pipe helical drives are based on independent passive wheels that are tilted an angle. One of the major problems of current helical wheel drives is their unstable traction force. In this paper, instead of allowing the wheels to rotate independently, they are synchronized by adding a timing belt. This small change will result in significant improvement which will be highlighted in this paper. In the proposed driving method, tracking force is analyzed together with a comprehensive set of traction force measurement experiments. Both analysis and experiments have shown that the proposed mechanism has great potential for in-pipe robot drive design.

A continuous finite-time control scheme for networked bilateral teleoperation is proposed in this brief. The terminal sliding mode technology is used and new master–slave torques are designed. With the new controller, the coordination error of the master manipulator and the slave manipulator converges to zero in finite time. Moreover, the reaching time and the sliding time can be derived. Finally, the comparisons are performed and simulations show the effectiveness of the proposed approach.