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sensor-based navigation of Omnidirectional Wheeled Robots Dealing with both Collisions and Occlusions

ROBOTICA 2020年第4期38卷 617-638页

作者： Khelloufi, Abdellah Achour, Nouara Passama, Robin Cherubini, Andrea Ctr Dev Adv Technol CDTA 20 Aout 1956 City Baba Hassen Algiers Algeria USTHB Fac Elect & Comp Sci BP32 EL ALIA Bab Ezzouar Algiers 16111 Algeria Univ Montpellier CNRS LIRMM Montpellier France

navigation tasks are often subject to several constraints that can be related to the sensors (visibility) or come from the environment (obstacles). In this paper, we propose a framework for autonomous omnidirectional wheeled robots that takes into account both collision and occlusion risk, during sensor-based navigation. The task consists in driving the robot towards a visual target in the presence of static and moving obstacles. The target is acquired by fixed - limited field of view - on-board cameras, while the surrounding obstacles are detected by lidar scanners. To perform the task, the robot has not only to keep the target in view while avoiding the obstacles, but also to predict its location in the case of occlusion. The effectiveness of our approach is validated through several experiments.

关键词： sensor-based navigation Omnidirectional wheeled robots Obstacle avoidance Visibility constraints Occlusions

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Comparative Study of Potential-based and sensor-based Surgical navigation in Several Liver Environments

Comparative Study of Potential-Based and Sensor-Based Surgic...

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23rd International Conference on Human-Computer Interaction (HCII)

作者： Kunii, Takahiro Asano, Miho Fujita, Kanako Tachibana, Katsunori Noborio, Hiroshi Kashina Syst Co Hikone Japan Kyoto Univ Hosp Preempt Med & Lifestyle Related Dis Res Ctr Kyoto Japan Osaka Electrocommun Univ Dept Comp Sci Shijonawate Japan Osaka Electrocommun Univ Dept Biomed Engn Shijonawate Japan

ISBN: (纸本)9783030784652;9783030784645

Medical navigators have gained recent attention for application in surgery to provide the surgeon with the position and orientation of malignant tumors as accurately as possible. Currently, extensive research is being conducted on producing surgical navigators;however, their practical application is difficult in the case of organ deformation. This study presents a medical navigation system using two types of algorithms to select a pathway from the scalpel tip near a malignant tumor in a 3D liver environment, which avoids blood vessels (arteries, veins, and portal veins) and the malignant tumor when they are regionally segmented inside the liver. The first algorithm involves potential-based navigation, in which the scalpel tip reaches its destination by adjusting the attraction to the destination (currently the malignant tumor) and the repulsion from the blood vessels. The second algorithm involves sensor-based navigation where the surgeon moves the scalpel in a straight line in the direction of the malignant tumor. When a blood vessel is encountered, the scalpel is moved in a clockwise or counterclockwise direction in a certain plane over a certain distance to avoid the blood vessel. It is then moved in a straight line in the direction of the malignant tumor again after approaching the malignant tumor monotonically or asymptotically. In this study, both navigation algorithms select a path near the malignant tumor in the 3D liver environments with diverse shapes and arrangements of blood vessels and malignant tumors. The potential-based navigation algorithm then selects a shorter straight path near the malignancy, but the direction of the incision varies in a complex manner. Lastly, the sensor-based navigation algorithm selects a longer circuitous path near the malignancy, but the incision direction is uniform.

关键词： Potential-based navigation sensor-based navigation Surgical navigation Collision-free and deadlock-free path Path length and shape

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Servo-level, sensor-based navigation Using Harmonic Potential Fields

Servo-level, Sensor-based Navigation Using Harmonic Potentia...

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European Control Conference (ECC)

作者： Masoud, Ahmad A. Ahmed, Mohanad Al-Shaikhi, Ali King Fahad Univ Petr & Minerals Dept Elect Engn Dhahran 31261 Saudi Arabia

ISBN: (纸本)9783952426937

This paper suggests an integrated navigation control system for time critical missions. The navigation control is derived from a harmonic potential field. It is designed to enable a mobile agent to proceed to a target point in an unknown environment without the need for a dedicated exploration and map-building stage. The agent, en route to the target, collects and processes only the necessary and sufficient sensory data needed to successfully execute the mission. Sensing, processing and all related activities needed to generate mobility are carried-out in real-time at the servo-level. The structure of the navigation control is described in details. Experimental results are provided as a proof of principle.

关键词： mobile robots navigation servomechanisms dedicated exploration harmonic potential field integrated navigation control system map-building stage mobile agent necessary and sufficient sensory data sensor-based navigation servo-level time critical mission Harmonic analysis Mobile robots navigation Robot kinematics Robot sensing systems

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Fuzzy sensor-based navigation with Neural Tracking Control of the Wheeled Mobile Robot

Fuzzy Sensor-Based Navigation with Neural Tracking Control o...

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13th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Szuster, Marcin Hendzel, Zenon Burghardt, Andrzej Rzeszow Univ Technol Dept Appl Mech & Robot PL-35959 Rzeszow Poland

ISBN: (纸本)9783319071756;9783319071763

navigation of the wheeled mobile robot in the unknown environment with simultaneous realisation of the generated trajectory, is one of the most challenging and up to date problems in the modern mobile robotics. In the article a new approach is presented to a collision-free trajectory generating for a wheeled mobile robot, realised in a form of the hierarchical control system with two layers. The first layer is a tracking control system, where the Neuro-Dynamic Programming algorithm in the Dual Heuristic Dynamic Programming configuration was applied. The second layer is a trajectory generator where the Fuzzy Logic systems were used. The presented control system generates and realises trajectory of the wheeled mobile robot within the complex task of goal-seeking and obstacle avoiding. The proposed hierarchical control system works on-line, its performance was verified using the wheeled mobile robot Pioneer 2-DX.

关键词： Neuro-Dynamic Programming Fuzzy System Mobile Robot Neural Networks Path Planning sensor-based navigation

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Deadlock-Free and Collision-Free Liver Surgical navigation by Switching Potential-based and sensor-based Functions 1

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Human-Computer Interaction Thematic Area Conference (HCI) Held as Part of the 22nd International Conference on Human-Computer Interaction (HCII)

作者： Noborio, Hiroshi Kawai, Kiyomi Watanabe, Kaoru Tachibana, Katsunori Kunii, Takahiro Mizushino, Kiminori Osaka Electrocommun Univ Dept Comp Sci Kiyotaki 1130-70 Shijyo Nawate Osaka 5720063 Japan Osaka Electrocommun Univ Dept Biomed Engn Kiyotaki 1130-70 Shijyo Nawate Osaka 5720063 Japan Kashina Syst Co Hirata Cho 116-22 Hikone Shiga 5220041 Japan Embedded Wings Co Ine 5-2-3 Mino Osaka 5620015 Japan

ISBN: (数字)9783030490652

ISBN: (纸本)9783030490645;9783030490652

In this study, we developed a deadlock-free and collision-free liver surgical navigation method by switching potential-based and sensor-based approaches. The potential-based approach selects a near-optimal route from a scalpel tip to an arbitrary neighbor position around a tumor in a 3D organ map converted from digital imaging and communications in medicine (DICOM) data captured by magnetic resonance imaging or computed tomography. However, among complex-shaped blood vessels, the approach sometimes loses the route. To overcome this drawback, we switch to the sensor-based approach. This approach always finds a route near a tumor. However, the path becomes longer. Therefore, when the potential-based approach recovers to find another path, we switch the sensor-based approach back to the potential-based approach. The usefulness of this switching method was carefully ascertained in several kinds of allocations of tumor and blood vessels.

关键词： Potential-based navigation sensor-based navigation Triangular polyhedron stereolithography Liver surgery navigator Deadlock-free property Local minima

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Combining the SLAM back and front ends with a joint vector-set distribution

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INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2025年第7期44卷 1231-1254页

作者： Inostroza, Felipe Adams, Martin Univ Chile Adv Min Technol Ctr AMTC Av Tupper 2007 Santiago 8370451 Chile Univ Chile Dept Elect Engn Av Tupper 2007 Santiago 8370451 Chile

The joint optimization of map management and map feature to measurement association, together with the trajectory and map states, within a single, unified, Bayesian, feature-based, simultaneous localization and mapping (SLAM) solution is addressed in this article. Remarkable progress in feature-based SLAM has been made in which, given data association, the SLAM problem can be solved by use of nonlinear least squares solvers, often referred to as the SLAM back-end. These methods rely on external methods to solve both the data association and map management problems, which are collectively incorporated into the SLAM front-end. SLAM convergence failures are common when these front-end routines fail, particularly when feature detection uncertainty increases. Therefore, this article introduces Joint, Vector-Set SLAM (JVS-SLAM), utilizing Bayes theorem to solve feature to measurement association, map management, and SLAM itself jointly, thus combining the SLAM back and front ends. Results will demonstrate equivalent or superior SLAM performance to state-of-the-art solutions, under varying odometry, spatial and detection measurement uncertainties, without reliance on data association decisions. Results are based on both simulations and the challenging EuRoC data set, in which a drone undergoing high accelerations, equipped with a stereo camera, performs SLAM. Since JVS-SLAM jointly provides a solution to the map feature to measurement association problem, its computational complexity is comparable with multi-hypothesis based solutions. Parallels between state-of-the-art map management and feature to measurement association methods and the detection statistics used within JVS-SLAM will be examined, with a view to reducing its complexity in the future.

关键词： Localization and mapping probability and statistical methods theoretical foundations sensor-based navigation vision and sensor-based control

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Distributed reactive motion control for dense cooperative sweep coverage of corridor environments by swarms of non-holonomic robots

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INTERNATIONAL JOURNAL OF CONTROL 2023年第3期96卷 554-567页

作者： Matveev, A. S. Konovalov, P. A. St Petersburg Univ Dept Math & Mech Univ Skii 28 St Petersburg 198504 Russia St Petersburg Natl Res Univ Informat Technol Mech Kronverksky Pr 49 St Petersburg 197101 Russia

Dubins-car like robots with limited control ranges have to autonomously form the densest net across a corridor environment, then to keep this formation, and to sweep the corridor with a given speed. The robots do not communicate with anybody, cannot distinguish between the partners, cannot play distinct roles in the team, and are unaware of the team size or corridor width. Every robot has access to the relative coordinates of the objects within a finite sensing range and measures its own speed. It is shown that the mission can be fully solved by a lower-level, continuous-time, and computationally inexpensive distributed control law. The proposed controller is common for all robots, individually operates at any of them and is reactive, i.e. it directly converts the current sensory data into the current control in a reflex-like fashion. The performance of the navigation algorithms is justified via a mathematically rigorous non-local convergence result for the corridors with straight parallel walls and is demonstrated via computer simulation tests in more complicated cases.

关键词： Non-holonomic robots multi-agent decentralised navigation and coordination sensor-based navigation sweep coverage

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IC-RCM: Intraoperative Real-Time Detection of 5D RCM-Misalignment in Robot-Assisted Ophthalmic Surgeries with a Single-Camera System 10

IC-RCM: Intraoperative Real-Time Detection of 5D RCM-Misalig...

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10th International Conference on Electrical Engineering, Control and Robotics (EECR)

作者： Alikhani, Alireza Fareghzadeh, Nida Inagaki, Satoshi Maier, Mathias Navab, Nassir Nasseri, M. Ali Tech Univ Munich Sch CIT Munich Germany Tech Univ Munich Sch Med & Hlth Munich Germany Tech Univ Munich Sch Med & HealthT Munich Germany

ISBN: (纸本)9798350370010;9798350370003

Robot-assisted ophthalmic surgery (RAOS) advancements have transformed precision in eye surgical procedures. RAOS offers unparalleled accuracy and dexterity, allowing for intricate maneuvers in delicate ocular structures with minimized invasiveness. However, ensuring the reliability and quality of the instruments' pivot point at the trocar, called Remote Center Motion (RCM), is imperative to uphold patient safety and surgical efficacy. Hence, real-time monitoring and tracing of RCM performance parameters are pivotal in minimizing surgical trauma and averting adverse outcomes. Our approach showcases a precise pipeline for recognizing RCM misalignment by integrating the robot's kinematic software data with neural network-based pose estimation methodologies with the mean absolute rotation error of 5.48, tested on a 23G surgical cannula with a diameter of 0.640 mm. This method uses a high-resolution camera at 4024 x 3036 capable of processing at 20 frames per second.

关键词： Robot Safety AI for Medical Robotics Medical Robots and Systems sensor-based navigation

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Envibroscope: Real-Time Monitoring and Prediction of Environmental Motion for Enhancing Safety in Robot-Assisted Microsurgery

Envibroscope: Real-Time Monitoring and Prediction of Environ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Alikhani, Alireza Inagaki, Satoshi Dehghani, Shervin Maier, Mathias Navab, Nassir Nasseri, M. Ali Tech Univ Munich Ophthalmol Dept Med Auton & Precis Surg Lab Munich Germany Tech Univ Munich Dept Comp Sci Munich Germany NSK Ltd Tokyo Japan Tech Univ Munich Chair Comp Aided Med Procedures & Augmented Real Munich Germany Johns Hopkins Univ Whiting Sch Engn Baltimore MD USA

ISBN: (纸本)9798350384581;9798350384574

Several robotic systems have emerged in the recent past to enhance the precision of micro-surgeries such as retinal procedures. Significant advancements have recently been achieved to increase the precision of such systems beyond surgeon capabilities. However, little attention has been paid to the impact of non-predicted and sudden movements of the patient and the environment. Therefore, analyzing environmental motion and vibrations is crucial to ensuring the optimal performance and reliability of medical systems that require micron-level precision, especially in real-life scenarios. To address this challenge, this paper introduces a novel environmental motion analysis system that employs a grid layout with distributed sensing nodes throughout the environment. This system effectively tracks undesired movements (motions) at designated locations and predicts upcoming motions using neural network-based approaches. The outcomes of our experiments exhibit promising prospects for real-time motion monitoring and prediction, which has the potential to form a solid basis for enhancing the automation, safety, integration, and overall efficiency of robot-assisted micro-surgeries.

关键词： Robot Safety AI for Medical Robotics Medical Robots and Systems sensor-based navigation

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sensor-based Mobile Robot navigation via Deep Reinforcement Learning

Sensor-based Mobile Robot Navigation via Deep Reinforcement ...

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IEEE International Conference on Big Data and Smart Computing (BigComp)

作者： Han, Seungho-Ho Choi, Ho-Jin Benz, Philipp Loaiciga, Jorge Korea Adv Inst Sci & Technol Sch Comp Daejoen South Korea Korea Adv Inst Sci & Technol Sch Elect Engn Daejoen South Korea

ISBN: (纸本)9781538636497

navigation tasks for mobile robots have been widely studied over past several years. More recently, there have been many attempts to introduce the usage of machine learning algorithms. Deep learning techniques are of special importance because they have achieved excellent performance in various fields, including robot navigation. Deep learning methods, however, require considerable amount of data for training deep learning models and their results may be difficult to interpret for researchers. To address this issue, we propose a novel model for mobile robot navigation using deep reinforcement learning. In our navigation tasks, no information about the environment is given to the robot beforehand. Additionally, the positions of obstacles and goal change in every episode. In order to succeed under these conditions, we combine several Q-learning techniques that are considered to be state-of-the-art. We first provide a description of our model and then verify it through a series of experiments.

关键词： mobile robot navigation deep reinforcement learning Q-learning sensor-based navigation

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