RRT Method Research Articles

Hybrid Sampling-Based Path Planning for Mobile Manipulators Performing Pick and Place Tasks in Narrow Spaces

A mobile manipulator is capable of traversing a vast area while performing manipulation tasks in confined spaces. However, the high degree of freedom presents a challenge for path planning. In this paper, a hybrid sampling-based path planning method is proposed for mobile manipulators performing pick and place tasks in confined spaces. This method employs a random sampling approach, yet differs from the traditional RRT method. Firstly, a sampling-based configuration generation method for mobile manipulators is proposed, with the objective of generating a valid, collision-free configuration with the end-effector at the desired pose. A path for the end-effector corresponding to the goal configuration is then planned using the RRT method. Secondly, an area-restricted approach that samples in the vicinity of the previous configuration is introduced to generate the next valid configuration. Subsequently, a cost computation rule is devised to identify the optimal subsequent configuration utilizing the trajectory of the end-effector as a guiding principle. Finally, the obtained path is smoothed. Simulations demonstrate that the proposed hybrid sample-based method is an effective solution to the path planning problem for mobile manipulators performing pick and place tasks in narrow spaces.

Ground vehicle path planning on Uneven terrain Using UAV Measurement point clouds

Abstract. The objective of this study is to develop a system to support rapid ground vehicle activities by planning safe travel routes for ground vehicles from point clouds of wide-area uneven terrain environments measured using UAVs. However, fast path planning is difficult in complex environments such as large, uneven terrain environments. Therefore, this paper proposes a new RRT method based on the RRT algorithm that can perform fast path planning, even in complex environments. In the proposed method, narrow areas that are difficult to be explored by ordinary RRTs are first identified in advance, and nodes are placed in these areas to guide the search. When searching with RRTs, the tree is extended via these guide nodes to efficiently traverse the narrow area. In the validation of the proposed method, a comparison was made with RRT and RRT-Connect in two environments, including narrow areas. The results show that the proposed method has a higher route discovery capability, at least two times fewer search nodes and five times faster path planning capability than other RRTs.

Quicker Path planning of a collaborative dual-arm robot using Modified BP-RRT* algorithm

Path-planning of an industrial robot is an important task to reduce the overall operation time. In industrial tasks, path planning is executed with lead-through programming, where in most cases the robot faces singulated object configurations. Cluttered environments demand path-planning algorithms, which are sensor driven, rather than pre-programmed. Path-planning algorithms, like RRT, and RRT* and their variants have inherent problems like the duration of a search and the creation of several node samples which may lead to longer path lengths. Back Propagation-Rapidly exploring Random Tree* (BP-RRT*) algorithm was a leap forward when an obstacle is enveloped with a sphere. Due to the spherical envelope of the obstacle, this method evaluates the connection between the path and obstacle in space with a spherical envelope using the triangular function and identifies the non-collision path in 3D space. This predicts the best non-collision path in the 3D workspace. The current state-of-the-art of BP-RRT* is limited to single-arm robots. A collaborative dual-arm robot faces more problems in path planning than a single-arm robot like inter-collision of manipulator arms apart from avoiding obstacles. A Modified BP-RRT* algorithm is proposed for the dual-arm collaborative robot has a pre-stage partition of grids that makes the computation faster, efficient, and collision-free compared to the traditional path planning algorithms namely RRT, RRT*, Improved RRT* and BP-RRT*. The algorithm is implemented in simulation as well as in physical implementation for ABB YuMi dual-arm collaborative robot and the typical length of the path of the proposed modified BP-RRT* method has reduced by 53.8% from the traditional RRT method, 6.95% from the RRT* method, 7.77% from improved RRT* method and 6.83% from the BP-RRT* method. Also, the average time to grasp has reduced by 17.84%, the typical duration for search has decreased by 33.45%, the number of node samples created has reduced by 14.79% from BP-RRT* algorithm.

Research of the Possibilities of Using a Rapidly Exploring Random Tree Algorithm in Solving Problems of Movement Planning of Autonomous Robots

The article is devoted to the analysis of features and evaluation of the prospects for using the RRT method in the problem of motion planning for autonomous robots. It is noted that the expansion of the areas of application of modern robotics is inextricably linked with an increase in the level of functionality and improvement of the designs of the created samples, for which the placement of a manipulator on a mobile platform becomes a typical layout. Based on a review of the literature and generalization of experimental data, it is shown that the use of the RRT method and its modifications opens up the fundamental possibility of developing a universal motion planner for mobile and manipulative robots, including systems with a manipulator on a mobile platform, as well as systems with a redundant or reconfigurable structure. Based on the results of the analysis, it was found that the effectiveness of the RRT method is largely determined by the declared parameter of the growth factor. A decentralized variant of the counter-growth RRT method is proposed, which makes it possible to plan the movements of autonomous mobile robots in the process of their mutual approach and subsequent docking. The fundamental possibility of automatic docking of autonomous robots in an environment with obstacles is confirmed by the results of a full-scale experiment.

Improved RRT global path planning algorithm based on Bridge Test

The RRT algorithm based on random sampling is widely used in planning problems with non-holonomic constraints. In indoor environments, narrow passages exist in the map, and the RRT method suffers from slow convergence speed and poor path quality. Additionally, the typical feature of large indoor room spaces with small exits creates traps where RRT can easily become stuck, making it difficult to find a path quickly. To solve the above problems, this paper proposes an improved RRT algorithm. This method first uses the simplified Bridge Test and point cloud clustering algorithm to locate the narrow passages on the map and place the root nodes in the narrow passage. Then grow multiple random trees from the root nodes, starting and endpoints. As the number of samples increases, the random trees gradually expand and connect to each other. The trees are connected to each other to build a complete path. Finally, the initial path is optimized and the final planning result is obtained. The simulation of the improved RRT, RRT*, RRT, and Bi-RRT is carried out. The simulation results show that the improved RRT algorithm proposed in this paper outperforms in terms of path length, number of exploring nodes, and processing time. We also tested 4 algorithms on a real robot, and the results prove the practical value of the improved algorithm.

Path planning of a 6-DOF measuring robot with a direction guidance RRT method

The path planning of a measuring robot is critical to automatic measurement, but it is hard to solve a global optimal path solution when it comes to scanning a complex body with many obstacles. To overcome this problem, a direction guidance Rapidly-exploring Random Tree algorithm (DG_RRT) is proposed. First, to improve the efficiency of the search process, the strategy of direction guidance is introduced for the initial path based on the traditional RRT algorithm. Second, invalid paths are simplified by linear processing. Third, to balance the length of the path and the planning time, generated paths are further corrected by adjusting the step size, optimizing threshold parameters, and smoothing the curve. To verify the suggested method, both numerical simulation and experimental analysis are carried out. The experimental results show that the average length of the paths (ALPs) of DG_RRT is 29.6% lower than that of the traditional RRT, 6.6% lower than that of RRT* and 43.0% lower than that of Q-learning (QL). The standard deviation (SD) of the path length of DG_RRT is 93.4% lower than that of traditional RRT, and 83.1% lower than that of RRT. The mean of planning time (MPT) of DG_RRT is 94.3% lower than that of RRT*, 95.5% lower than that of QL. The number of discrete points on the path of DG_RRT is 81.4% lower than that of traditional RRT, 86.0% lower than that of RRT* and 91.7% lower than that of QL. It demonstrates that the DG_RRT is superior to other traditional methods.

Research on the Bias Sampling RRT Algorithm for Supermarket Chain Distribution Routes under the O2O Model

The purpose of this article is to propose the Bias Sampling RRT algorithm and use it as an optimization algorithm for supermarket chain distribution routes under the O2O model. As a retail store in the transformation and upgrading of chain stores, the actual terrain factors in distribution directly affect the timely delivery of goods from online to offline. The Bias Sampling RRT algorithm, as a path search method for time window vehicle routing problems, can find the optimal path that meets time window constraints. The applicability and effectiveness of the Bias Sampling RRT algorithm have been demonstrated through map simulation calculations. The simulation results show that compared with the RRT method, the Bias Sampling RRT algorithm has a shorter distribution path and shorter distribution time. This method is very suitable for the distribution activities of chain supermarkets or single store retail enterprises in the complex transformation and upgrading of actual terrain.

Comparison of Quality of Life of Dialysis Treatments: The Case of Ankara Province

Objective: In this cross-sectional study, the quality of life of the patients who received Central hemodialysis (CH), Home Hemodialysis (HH) and Peritoneal Dialysis (PD) treatments, which are the RRT methods applied in ESRD in Türkiye, compared. This study aimed to offer suggestions for disseminating the application of the treatment method that provides life comfort. Materials and Methods: Kidney Disease Quality of Life scale KDQOL 36 was applied to patients in Ankara diagnosed with ESRD and receiving central hemodialysis, home hemodialysis and peritoneal dialysis treatment. The scale was applied by face-to-face interview method between 10.02.2022 and 01.05.2022. A simple random sampling method was used to determine the sample size, and all patients (n:574) with the sample size selected within the scope of the study were reached. In the evaluation of statistical tests, the level of significance was taken as α 0,05. Results: It was observed that the mean quality of life of the physical and mental health components, which indicate the general quality of life of the patients, were below the average level with the values of 37.7±9.8 and 42.4±9.3, respectively. The mean of the effects of kidney disease sub-dimension was 58.9±24.5; The mean of the symptom list sub-dimension of kidney disease was 66.0±21.9. Conclusion: When the mean values of the sub-dimensions of the scale are evaluated as a whole, it is considered that the quality of life of the patients receiving dialysis treatment is low. Since home hemodialysis is superior to other types of dialysis in all sub-dimension mean scores of the scale, it is recommended that the Social Security Institution make encouraging regulations in the Health Implementation Communiqué to disseminate this practice.

Path Planning for Robotic Manipulator in Complex Multi-Obstacle Environment Based on Improved_RRT

To plan a successful and practically executable path for a manipulator in a complex obstacle environment, the Improved_RRT method is proposed. In this article, we develop the collision detection model between the manipulator and obstacle based on the cylinder and sphere bounding box, and the shortest distance between the link and obstacle at each moment is obtained. Afterward, hybrid constrained sampling is used instead of original random sampling. The distribution of nodes obtained by sampling is close to the passages between obstacles. During the sampling process, the forward search process is accelerated. In the expansion, we propose a novel approach of RRT_Connect in collaboration with the artificial potential field method. Meanwhile, the adaptive gravitational field, dynamic step size, and new node constraint strategy are adopted. In the process of expansion, the algorithm uses the information of the environment and nodes to expand to the target area in a short time, which reduces the excessive exploration and collision area expansion. Considering the low success rate of algorithm planning in complex, multiobstacle and dynamic environments, local minimum processing and a dynamic path planning method are proposed, which generate double trees in the Cartesian and configuration spaces, respectively, for local path replanning. The improved algorithm is more robust to the singular problems of the manipulator, and the path is smoother after pruning optimization. Simulation results show that, compared with other algorithms, the proposed method can effectively plan a safe and optimal obstacle avoidance path with the best comprehensive performance. Experiments on the actual robotic manipulator platform further prove the efficiency of our method.

Patients’ Experience of Undergoing Peritoneal Dialysis about entered Peritoneal Dialysis: A Qualitative Study on Iranian patients

Training and involving patients, especially patients with chronic renal failure, in the selection of treatments can effectively increase their satisfaction with treatment and life expectancy and also improve their quality of life. This study hence aimed to explain Iranian patients’ experience of undergoing peritoneal dialysis (PD). This qualitative study was conducted based on the conventional content analysis. Based on the review and analysis of transcribed interviews, three main categories were extracted from patients’ experience: 1- random familiarity with PD, 2- mandatory familiarity with PD, and 3- optional familiarity with PD. Based on the study findings, it can be concluded that none of the RRT methods is superior to the others. All patients with CKD should receive enough information about different types of RRT before undergoing dialysis, so that they can more easily adapt to the treatment, enjoy a higher quality of life, and experience a higher quality of life.

An obstacle avoidance algorithm for space hyper-redundant manipulators using combination of RRT and shape control method

AbstractThis paper proposes a kinematic obstacle avoidance algorithm for Space hyper-redundant manipulators, and its basic idea is to use a static and a dynamic curve to constrain the macroshape of the manipulators simultaneously. The static curve is constructed based on a traditional rapidly exploring random tree algorithm, and a backbone curve is utilized as the dynamic curve. For these two curves, two novel shape control methods are proposed to accomplish the shape constraining process. Finally, we verify the reliability and effectiveness of our algorithm through simulations.

Replacement renal therapy in the treatment of patients with a severe course of the new coronavirus infection

Objective: to study the use of RRT methods and their influence on the results of treatment of patients with severe COVID-19.Subjects and methods. We retrospectively analyzed the data of 283 patients with COVID-19 in the intensive care units of Moscow City Hospital no. 40 in 2020 who had received RRT as one of the treatment methods.Results. Frequency of RRT in COVID-19 patients in ICU of Moscow City Hospital no. 40 for 2020 made 5.7% (504 out of 8.711 patients treated in ICU received RRT). In 86% of cases, RRT was performed for renal indications. At the time of initiation of RRT, the studied groups did not differ according to SOFA score. The frequency of using dialysis units with high and low cut-off point in the groups of survived and deceased patients differed significantly. The surgery itself started at relatively the same time from the onset and statistically significantly earlier in the group of survivors from the beginning of tracheal intubation (4.9 ± 0.5 vs 6.8 ± 0.3 days, p = 0.0013). Against the background of ongoing therapy, overall severity of the state progressed in the group of deceased patients to 9.9 ± 0.2 SOFA scores, while in the group of survivors there was an improvement to 6.1 ± 0.4 scores.

THE GENERAL PRINCIPLES OF THE COMPLEX PROCESS OF THE RESTORATION-RECONSTRUCTIVE TRANSFORMATIONS OF THE HISTORICAL CENTERS OF SMALL TOWNS

The article gives the definition of «restoration-reconstructive transformation» (RRT). Four interconnected systemic levels of the complex process of restoration- reconstructive transformations of the historical centers of small towns have been identified, namely: urban, volumetric, functional and socio-economic. The general principles of the complex process of RRT of the historical centers of small towns are formulated. These are the principles of: «cumulative development» (the accumulation of positive properties that together contribute to its qualitative change, a combination of «traditions» and «innovations»); «contextual addition» (introduction of the necessary new buildings and spaces according to the formed context); «attractive spatial disclosure» (increasing the attractiveness of the historical center) and «multi-comfort» (providing a qualitatively different duration of stay of different people in the historical center). The principles are recommended for the implementation of qualitative changes in historic centers at all defined four systemic levels. They are universal for the historical environment, of any degree of value and destruction, when carrying out the restoration-reconstructive transformations using preserving and restoring, as well as renewing and transforming methods, to improve its quality and transition to a multi-comfortable one. The principle of «cumulative development» is highlighted as the main one in the implementation of the restoration-reconstructive transformations of the historical city centers. The conditional correspondence of the general principles and methods of RRT was determined. For the principles of «cumulative development», «attractive spatial disclosure» and «multi-comfort» – all preserving, restoring, renewing and transforming RRT methods of urban level and the corresponding ones from the volumetric and functional levels, depending on the degree of value and destruction of the historical environment. For the principle of «contextual addition» – restoring, renewing and transforming RRT methods of urban level (regeneration, revalorization, renewal, revitalization, transformation, renovation) with the corresponding methods of volumetric and functional levels.

Acute Renal Injury in Cardiac Surgery Patients

Background. Acute kidney injury following cardiac surgery remains a common and serious complication.Aim of study. To identify risk factors for the development and morphological features of acute renal injury, to assess the use of renal replacement therapy in patients after cardiac surgery.Material and methods. The study involved 66 patients who were treated in the Department of Cardiac Resuscitation of the N.V. Sklifosovsky Research Institute for Emergency Medicine from 2009 to 2018. Of these, 45 men (68.2%) and 21 women (31.8%). The mean age of the patients was 56.3±13.2 years. Clinical and anatomical analysis of material from 19 deceased patients was carried out. Depending on the use of methods of renal replacement therapy, patients were divided into two groups: Group 1 included 23 patients with acute renal injury requiring the use of renal replacement therapy; Group 2 included 43 patients where methods of renal replacement therapy were not used.Results. Hospital mortality in Group 1 was lower (34.8 and 41.9%, respectively), however, the differences were statistically insignificant (p=0.372). To identify the factors in the development of acute renal damage, a stepwise regression analysis was performed by constructing a regression model of Cox proportional hazards. Age, history of chronic kidney disease, serum creatinine level on the first day after surgery, severity of the condition according to the APACHE-II scale, increased lactate level on day 2 of the postoperative period, decreased urine output on the first day after surgery were statistically significant.Conclusion. Risk factors for the development of ARI after cardiac surgery under cardiopulmonary bypass are advanced age, CKD in history, the severity of the patient’s condition, assessed by the APACHE-II scale, increased serum creatinine on the first day after surgery, increased lactate on day 2 of the postoperative period, a decreased diuresis on day 1 after surgery. The use of RRT in patients after surgery under the conditions of AC was accompanied by a tendency to improve treatment results: in-hospital mortality in the group of patients who underwent RRT was 34.8% versus 41.9% in the group without RRT methods. Morphological and functional features of renal failure in patients with ARI were preceding chronic renal pathological processes of different etiology, mainly affecting the glomeruli, vessels and stroma, as well as acute pathological processes aggravating ARI (dyscirculatory disorder, degenerative changes, necrosis and necrobiosis tubular epithelium).

Path planning for indoor Mobile robot based on deep learning

This paper aims to give an optimal path planning of a mobile robot in a known indoor environment. An algorithm based on deep learning, ray tracing algorithm, waiting rule, and Rapidly-exploring Random Tree is proposed to solve the problem of obstacle avoidance and path planning. Firstly, GoogLeNet is used to classify obstacles. Here, it helps to distinguish between static and dynamic obstacles. Secondly, for the static obstacle avoidance, the ray tracing algorithm is proposed to avoid the obstacles which are identified by GoogLeNet. And for the dynamic obstacle avoidance, this paper proposed a waiting rule for dynamic obstacle avoidance. Thirdly, the RRT method plans a path from the start point to the goal point. The novelty of this paper is that the type of obstacles is distinguished by deep learning, and the two different kinds of obstacles used ray tracing algorithm and waiting rule to avoid obstacles collision, respectively. In experimental results, rapidly-exploring random tree is compared with genetic algorithm, and particle swarm optimization method in static environment, and it is compared with artificial potential field approach in dynamic environment. Experiments are carried out in the two-dimensional environment and successfully applied to the path planning of mobile robots in multi-obstacles environment, and they prove the feasibility of the algorithm.

LSTM ネットワークを用いたロボットの移動経路の学習と探索

We propose a novel robot path planning method combining RRT and LSTM network. In this method, numerous and good paths are generated in the robot configuration space by RRT method, a small size LSTM network is trained by them. By the proposed method, the difficulty of general methods with LSTM network, i.e. “the acquisition of a large amount of training data” is overcame. Moreover, the difficulty of general random based methods, i.e. “the reproducible path generation” is enabled with high-speed.

Pharmacokinetic assessment in patients receiving continuous RRT: perspectives from the Kidney Health Initiative.

The effect of AKI and modern continuous RRT (CRRT) methods on drug disposition (pharmacokinetics) and response has been poorly studied. Pharmaceutical manufacturers have little incentive to perform pharmacokinetic studies in patients undergoing CRRT because such studies are neither recommended in existing US Food and Drug Administration (FDA) guidance documents nor required for new drug approval. Action is urgently needed to address the knowledge deficit. The Kidney Health Initiative has assembled a work group composed of clinicians and scientists representing academia, the FDA, and the pharmaceutical and dialysis industries with expertise related to pharmacokinetics, AKI, and/or CRRT. The work group critically evaluated key considerations in the assessment of pharmacokinetics and drug dosing in CRRT, practical constraints related to conducting pharmacokinetic studies in critically ill patients, and the generalizability of observations made in the context of specific CRRT prescriptions and specific patient populations in order to identify efficient study designs capable of addressing the knowledge deficit without impeding drug development. Considerations for the standardized assessment of pharmacokinetics and development of corresponding drug dosing recommendations in critically ill patients with AKI receiving CRRT are proposed.

테스트 목표 기반의 향상된 RRT 확장 기법을 이용한 Stateflow 모델 테스트 케이스 생성

This paper proposes a test case generation method for Stateflow model using the extended RRT method. The RRT method which has been popularly used for planning paths for complex systems also shows a good performance for test case generation. However, it does not consider the test coverage which is important for test case generation. The proposed extension method hires the concept of test goal achievement to increase test coverage and drives RRT extension in the direction that increases the goal achievement. Considering the concept, a RRT distance metric, random node generation method and modified RRT extension algorithm are proposed. The effectiveness of proposed algorithm is compared with that of the typical RRT algorithm through the experiment using the practical automotive ECUs.

Making Use of “Benford’s Law” for the Randomized Response Technique

In this article, “Benford’s law” is applied to the “randomized response technique” (RRT) to increase the validity of answers to sensitive questions. Using the Newcomb–Benford distribution as a randomizing device has several advantages. It is easy to explain and follow the procedure, as no physical device such as a coin or a dice is necessary and the method guarantees full anonymity. As is well known, the price for the anonymity of the RRT is a decrease in the efficiency of the estimator. However, because of the subjective overestimation of certain numbers (Benford illusion), the conflict between the variance of the estimates and the degree of anonymity is less pronounced compared to other RRT methods. The suggested RRT variant has the potential to improve the efficiency of the estimator. Moreover, the assumption is that this method works well with self-administered questionnaires.

迷路探索法に基づく６自由度アーム型ロボットの動作計画

In this paper, we propose a fast motion planning method for 6 DOF manipulator based on a maze-searching algorithm. Proposed method is utilizing the CPFS (Closest Point First Search) algorithm similar to the Bug2 algorithm proposed by Lumelsky. We have modified CPFS algorithm with FAP (Footprint Avoidance Procedure) in order to guarantee that the planning does not fall into the deadlock situation. At the beginning of the planning, the initial configuration of 6 DOF robot moves straight toward goal configuration . When the path meets collision configuration, the path is generated along the boundary between free- and collision-configuration. Using computer simulation, we evaluate the proposed method with calculation time. As a result, the proposed method can generate a path with 10 times shorter than the RRT method.