Advances in Robotics & Automation

The aim of disseminating this research article is to introduce a novel path planner method in detail and argue that it performs as well as other offline path planners in terms of analyzing and constructing collision-free trajectories in addition to shortest possible path from start to goal configurations. Our novel path planner is able to build optimal trajectories in terms of the shortest length as well as near miss avoidance route from the initial to the goal configuration. It allows a moving point robot to make a proper transition from its assigned goal toward a collision-free path in the reasonable time frame, successfully. As an offline path planner, our planner performs the operation of analyzing the environment on static workspaces with the fixed and known initial and the goal configurations and computing optimal trajectories, using global information about the environment. As a feature of novelty, our planner benefits of using a limited amount of global knowledge, however. This helps moving robot to allocate less system resources such as memory which leads the robot to perform the process of building optimal trajectories more efficiently. The shortest route is considered to be secure enough to enable mobile robot to maneuver among obstacles in workspace without involving any near misses. Our novel path planner is able to process any types of obstacles in terms of shapes and edges flawlessly. For instance, it can be applied on any spiral or curved obstacles successfully. This novelty feature distinguishes our offline path planner from the majority of other planners that are solely able to compute the optimal trajectories for certain obstacle shapes such as polygonal obstacles. Moreover, this paper attempts to evaluate our novel path planner algorithm abilities and skills by examining it on selected workspaces. We also assess our novel path planner through comparing it with other planners to reveal its efficiency in terms of ability to route optimal trajectories in regards to minimizing trajectory distances from initial to the goal configurations as well as the reliability and safety of the optimal processed path.

This article presents a novel offline path planner method to yield a collision-free trajectory among groups of obstacles in a static workspace. It enables a single holonomic point robot acting in a static environment including a fixed initial and goal configurations to achieve its goal toward a collision-free trajectory. In developing our novel path planner, we focused to elevate features that help the planner to route in a wide variety of different situations in regards to lowering the processing time needed for analyzing the workspace and determination of ultimate trajectory. Unlike to some other planners that are able to be applied on some certain obstacle shales such as polygonal, our planner is skillful enough to analyze any types of obstacles, such as circular, spiral, and curved edged obstacles successfully. To increase the performance of our proposed offline path planner, we defined and benefitted from introduction of parameters that help to achieve the best possible results among different scenarios in workspace components arrangements as well as reducing the planner needing to access system resources such as memory or processing unit to analyze the workspace while computing the shortest collision-free path from start point to the goal configuration. The novel planner analyses and transforms the two dimensional representation of the environment into a roadmap consisting a graph of nodes along with all possible routes from the moving robot’s initial point into the goal configuration. In order to manage some of the popular problems such as being trapped inside a U-shaped obstacle or routing in narrow pathways among obstacles, that challenge other offline path planners such as Potential Field planner are facing, we used a multi-layer approach in form of different stages to help the planner considering all possible circumstances and hence, compute the best possible route.

This paper presents the modelling and the control architecture of an Autonomous Underwater Vehicle for Intervention (I-AUV). Autonomous underwater manipulation with free-floating base is still an open topic of research, far from reaching an industrial product. Dynamic manipulation tasks, where relevant vehicle velocities are required during manipulation, over an additional challenge. In this paper, the accurate modelling of an I-AUV is described, not neglecting the interaction with the fluid. A grasp planning strategy is proposed and integrated in the control of the whole system. The performances of the I-AUV have been analysed by means of simulations of a dynamic manipulation task.

Since its inception in the 1980s, robotic surgery has rapidly progressed into a variety of surgical fields including general surgery, urology, gynecology, cardiac surgery as well as thoracic surgery. In this review, we highlight the robotic assisted thoracic surgery (RATS) in primary lung cancer, focusing on basic surgical technique, anesthetic considerations, outcome, complications, and cost. We discuss our experience as a tertiary urban referral center that routinely performs robotic lung resections. Finally, we discuss potential hurdles and the future directions in robotic surgery.

This paper presents a robust algorithm for object detection and tracking using MATLAB. This program captures a single image using a webcam attached to the laptop. The captured image is processed to find a predefined object. The centroid of the object is calculated. Subsequent images are then acquired. Each time a new image is acquired, the predefined object and its centroid is extracted and compared to the centroid of the previous image. The differences in the x and y coordinates of the centroids are used to determine the direction of movement of the Irobot Create. Once the algorithm determines the direction of movement, the program issues the move command wirelessly to the robot with the aid of a Bluetooth Adapter Module.

A new concept for developing hexapod robots using eccentric wheels is proposed in this work. Compared with the RHex robot, the proposed hexapod robot can greatly reduce the bumping of the robot body in both smooth ground and rocky terrain. Also, the developed hexapod robot possesses significant advantages over those with common circular wheels in traversing rocky and uneven terrain. Also, the control of the proposed hexapod robot is simple because each eccentric wheel has only one degree of freedom. This work focuses on the kinematics analysis of the proposed hexapod robot. Two types of gaits respectively named as the alternating tripod gait and the hexapod gait are proposed. With the alternating tripod gait, the robot can move continuously. But the hexapod gait is helpful in overcoming the resistant torque caused by the weight on the eccentric wheels. Besides, the effect of the eccentricity on the motion of the robot is analyzed. The proposed hexapod robot can be used to detect the gas in underground mines.