An Analysis Review: Optimal Trajectory for 6-DOF-based Intelligent Controller in Biomedical Application

With technological advancements and the development of robots have begun to be utilized in numerous sectors, including industrial, agricultural, and medical. Optimizing the path planning of robot manipulators is a fundamental aspect of robot research with promising future prospects. The precise robot manipulator tracks can enhance the efficacy of a variety of robot duties, such as workshop operations, crop harvesting, and medical procedures, among others. Trajectory planning for robot manipulators is one of the fundamental robot technologies, and manipulator trajectory accuracy can be enhanced by the design of their controllers. However, the majority of controllers devised up to this point were incapable of effectively resolving the nonlinearity and uncertainty issues of high-degree freedom manipulators in order to overcome these issues and enhance the track performance of high-degree freedom manipulators. Developing practical path-planning algorithms to efficiently complete robot functions in autonomous robotics is critical. In addition, designing a collision-free path in conjunction with the physical limitations of the robot is a very challenging challenge due to the complex environment surrounding the dynamics and kinetics of robots with different degrees of freedom (DoF) and/or multiple arms. The advantages and disadvantages of current robot motion planning methods, incompleteness, scalability, safety, stability, smoothness, accuracy, optimization, and efficiency are examined in this paper

Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control

This paper provides an overview of the current state-of-the-art in selective harvesting robots (SHRs) and their potential for addressing the challenges of global food production. SHRs have the potential to increase productivity, reduce labour costs, and minimise food waste by selectively harvesting only ripe fruits and vegetables. The paper discusses the main components of SHRs, including perception, grasping, cutting, motion planning, and control. It also highlights the challenges in developing SHR technologies, particularly in the areas of robot design, motion planning and control. The paper also discusses the potential benefits of integrating AI and soft robots and data-driven methods to enhance the performance and robustness of SHR systems. Finally, the paper identifies several open research questions in the field and highlights the need for further research and development efforts to advance SHR technologies to meet the challenges of global food production. Overall, this paper provides a starting point for researchers and practitioners interested in developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic

Path Planning for a 6 DoF Robotic Arm Based on Whale Optimization Algorithm and Genetic Algorithm

The trajectory planning for robotic arms is a significant area of research, given its role in facilitating seamless trajectory execution and enhancing movement efficiency and accuracy. This paper focuses on the development of path planning algorithms for a robotic arm with six degrees of freedom. Specifically, three alternative approaches are explored: polynomial (cubic and quantic), Whale Optimization Algorithm (WOA), and Genetic Algorithm (GA). The comparison of outcomes between different methods revealed that polynomial methods were found to be more straightforward to implement, albeit constrained by the intricacy of the pathway. Upon examining the functioning of the WOA, it has been shown that it is well suited for all types of pathways, regardless of their level of complexity. In addition, when GA is applied, it has been shown less smoothness than WOA but also less complexity. In brief, WOA is deemed superior in the path planning process since it is more thorough in determining the optimal path due to the conical spiral path technique it employs in offering optimized path planning. in comparison to GA, WOA is better in implementation speed and accuracy. However, GA is smoother in start and finish path

Path Planning for a 6 DoF Robotic Arm Based on Whale Optimization Algorithm and Genetic Algorithm

The trajectory planning for robotic arms is a significant area of research, given its role in facilitating seamless trajectory execution and enhancing movement efficiency and accuracy. This paper focuses on the development of path planning algorithms for a robotic arm with six degrees of freedom. Specifically, three alternative approaches are explored: polynomial (cubic and quantic), Whale Optimization Algorithm (WOA), and Genetic Algorithm (GA). The comparison of outcomes between different methods revealed that polynomial methods were found to be more straightforward to implement, albeit constrained by the intricacy of the pathway. Upon examining the functioning of the WOA, it has been shown that it is well suited for all types of pathways, regardless of their level of complexity. In addition, when GA is applied, it has been shown less smoothness than WOA but also less complexity. In brief, WOA is deemed superior in the path planning process since it is more thorough in determining the optimal path due to the conical spiral path technique it employs in offering optimized path planning. in comparison to GA, WOA is better in implementation speed and accuracy. However, GA is smoother in start and finish path

Applications of parallel computing in robotics problems

"December 2013.""A Thesis presented to the Faculty of the Graduate School University of Missouri In Partial Fulfillment Of the Requirements for the Degree Master of Science."Thesis advisor: Dr. Guilherme N. DeSouza.Many typical robotics problems involve search in high-dimensional spaces, where real-time execution is hard to be achieved. This thesis presents two case studies of parallel computation in such robotics problems. More specifically, two problems of motion planning-the Inverse Kinematics of robotic manipulators and Path Planning for mobile robots-are investigated and the contributions of parallel algorithms are highlighted. For the Inverse Kinematics problem, a novel and fast solution is proposed for general serial manipulators. This new approach relies on the computation of multiple (parallel) numerical estimations of the inverse Jacobian while it selects the current best path to the desire con- figuration of the end-effector. Unlike other iterative methods, our method converges very quickly, achieving sub-millimeter accuracy in 20.48ms in average. We demonstrate such high accuracy and the real-time performance of our method by testing it with six different robots, at both non-singular and singular configurations, including a 7-DoF redundant robot. The algorithm is implemented in C/C++ using a configurable number of POSIX threads, and it can be easily expanded to use many-core GPUs. For the Path Planning problem, a solution to the problem of smooth path planning for mobile robots in dynamic and unknown environments is presented. A novel concept of Time-Warped Grids is introduced to predict the pose of obstacles on a grid-based map and avoid collisions. The algorithm is implemented using C/C++ and the CUDA programming environment, and combines stochastic estimation (Kalman filter), Harmonic Potential Fields and a Rubber Band model, and it translates naturally into the parallel paradigm of GPU programing. The proposed method was tested using several simulation scenarios for the Pioneer P3- DX robot, which demonstrated the robustness of the algorithm by finding the optimum path in terms of smoothness, distance, and collision-free either in static or dynamic environments, even with a very large number of obstacles.Includes bibliographical references (pages 70-78)

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored