Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems

In general, modern operating systems can be divided into two essential parts, real-time operating systems (RTOS) and general-purpose operating systems (GPOS). The main difference between GPOS and RTOS is the system istime-critical or not. It means that; in GPOS, a high-priority thread cannot preempt a kernel call. But, in RTOS, a low-priority task is preempted by a high-priority task if necessary, even if it’s executing a kernel call. Most Linux distributions can be used as both GPOS and RTOS with kernel modifications. In this study, two Linux distributions, Ubuntu and Pardus, were analyzed and their performances were compared both as GPOS and RTOS for path planning of the multi-robot systems. Robot groups with different numbers of members were used to perform the path tracking tasks using both Ubuntu and Pardus as GPOS and RTOS. In this way, both the performance of two different Linux distributions in robotic applications were observed and compared in two forms, GPOS, and RTOS.

Hyper-Redundant Manipulator Capable of Adjusting Its Non-Uniform Curvature with Discrete Stiffness Distribution

Hyper-redundant manipulators are widely used in minimally invasive surgery because they can navigate through narrow passages in passive compliance with the human body. Although their stability and dexterity have been significantly improved over the years, we need manipulators that can bend with appropriate curvatures and adapt to complex environments. This paper proposes a design principle for a manipulator capable of adjusting its non-uniform curvature and predicting the bending shape. Rigid segments were serially stacked, and elastic fixtures in the form of flat springs were arranged between hinged-slide joint segments. A manipulator with a diameter of 4.5 mm and a length of 28 mm had been fabricated. A model was established to predict the bending shape through minimum potential energy theory, kinematics, and measured stiffnesses of the flat springs. A comparison of the simulation and experimental results indicated an average position error of 3.82% of the endpoints when compared to the total length. With this modification, the manipulator is expected to be widely used in various fields such as small endoscope systems and single-port robot systems.

Mobile Robots and Cobots Integration: A Preliminary Design of a Mechatronic Interface by Using MBSE Approach

Enabling technologies that drive Industry 4.0 and smart factories are pushing in new equipment and system development also to prevent human workers from repetitive and non-ergonomic tasks inside manufacturing plants. One of these tasks is the order-picking which consists in collecting parts from the warehouse and distributing them among the workstations and vice-versa. That task can be completely performed by a Mobile Manipulator that is composed by an industrial manipulator assembled on a Mobile Robot. Although the Mobile Manipulators implementation brings advantages to industrial applications, they are still not widely used due to the lack of dedicated standards on control and safety. Furthermore, there are few integrated solutions and no specific or reference point allowing the safe integration of mobile robots and cobots (already owned by company). This work faces the integration of a generic mobile robot and collaborative robot selected from an identified set of both systems. The paper presents a safe and flexible mechatronic interface developed by using MBSE principles, multi-domain modeling, and adopting preliminary assumptions on the hardware and software synchronization level of both involved systems. The interface enables the re-using of owned robot systems differently from their native tasks. Furthermore, it provides an additional and redundant safety level by enabling power and force limiting both during cobot positioning and control system faulting.

Artificial Intelligence-a Paradigm shift in Health Care Management

Artificial Intelligence (AI) is gradually changing the practice of surgery with the advanced technological development of imaging, navigation, and robotic intervention. In this article, the recent successful and influential applications of AI in surgery are reviewed from pre-operative planning and intra-operative guidance to the integration of surgical robots. It ends with summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery. Robotic surgery is the use of computer technologies working in conjunction with robot systems to perform medical procedures. The technology is also known as computer-aided surgery and robot-assisted surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments in the field of Neuro Surgery.

Hunting strategy for multi-robot based on wolf swarm algorithm and artificial potential field

The cooperation and coordination in multi-robot systems is a popular topic in the field of robotics and artificial intelligence, thanks to its important role in solving problems that are better solved by several robots compared to a single robot. Cooperative hunting is one of the important problems that exist in many areas such as military and industry, requiring cooperation between robots in order to accomplish the hunting process effectively. This paper proposed a cooperative hunting strategy for a multi-robot system based on wolf swarm algorithm (WSA) and artificial potential field (APF) in order to hunt by several robots a dynamic target whose behavior is unexpected. The formation of the robots within the multi-robot system contains three types of roles: the leader, the follower, and the antagonist. Each role is characterized by a different cognitive behavior. The robots arrive at the hunting point accurately and rapidly while avoiding static and dynamic obstacles through the artificial potential field algorithm to hunt the moving target. Simulation results are given in this paper to demonstrate the validity and the effectiveness of the proposed strategy.

Adaptive Motion Control Middleware for Teleoperation Based on Pose Tracking and Trajectory Planning

Concurrent with autonomous robots, teleoperation gains importance in industrial applications. This includes human–robot cooperation during complex or harmful operations and remote intervention. A key role in teleoperation is the ability to translate operator inputs to robot movements. Therefore, providing different motion control types is a decisive aspect due to the variety of tasks to be expected. For a wide range of use-cases, a high degree of interoperability to a variety of robot systems is required. In addition, the control input should support up-to-date Human Machine Interfaces. To address the existing challenges, we present a middleware for teleoperation of industrial robots, which is adaptive regarding motion control types. Thereby the middleware relies on an open-source, robot meta-operating system and a standardized communication. Evaluation is performed within defined tasks utilizing different articulated robots, whereby performance and determinacy are quantified. An implementation sample of the method is available on: https://github.com/FAU-FAPS/adaptive_motion_control.

Leaderless Maneuver Guidance and Event-Triggered Formation Control for Distributed Multi-Space-Robot Systems

In this paper, the distributed displacement-based formation and leaderless maneuver guidance control problems of multi-space-robot systems are investigated by introducing event-triggered control update mechanisms. A distributed formation and leaderless maneuver guidance control framework is first constructed, which includes two parallel controllers, namely, an improved linear quadratic regulator and a distributed consensus-based formation controller. By applying this control framework, the desired formation configuration of multi-space-robot systems can be achieved and the center of leaderless formation can converge to the target point globally. Second, a pull-based event triggering mechanism is introduced to the distributed formation controller, which makes the control update independent of the events of neighboring robots, avoids unnecessary control updates, and saves the extremely limited energy of space robots. Furthermore, the potential Zeno behaviors have been excluded by proving a positive lower bound for the inter-event times. Finally, numerical simulation verifies the effectiveness of the theoretical results.