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8th Smart Trends in Computing and Communications (SmartCom)

作者： Patil, Aditya Chandolkar, Shreyas Kothawade, Pranit Shaikh, Sohel Jaiswal, Rupesh Patwardhan, Aditya SCTRs Pune Inst Comp Technol Dept Elect & Telecommun Pune Maharashtra India Espressif Syst Pune Maharashtra India

ISBN: (纸本)9789819713226;9789819713233

This paper examines various bug and SWARM algorithms for robot navigation. We provide a comprehensive summary of initial bug algorithms, differences, and advancements, along with a comparative study. The context and motivation for different bug algorithms are provided for navigation in an environment with obstacles and reviews over 20 contributions made in the time frame of 2002 to 2023. These contributions are categorized based on their selection of bug algorithm, SWARM compatibility, inter-robot detection, etc. We also discuss the real-life requirements of a navigation algorithm and review each work based on said criteria. Possible drawbacks and issues are also discussed.

关键词： bug algorithm SWARM Mapping Navigation Inter-robot communication Multi-robot systems

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Human Robot Interaction using Android and Pointbug algorithm 3

Human Robot Interaction using Android and PointBug Algorithm

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3rd International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Choudhury, Nupur Mandal, Rupesh Assam Don Bosco Univ Comp Sci Engn & IT Gauhati India Sikkim Manipal Inst Technol Comp Sci & Engn Sikkim India

ISBN: (纸本)9789380544199

This paper deals with the project that deals with the development of a robot, particularly a Board Of Education bot that is controlled via an android application. The robot is built in such a way that it can be controlled both using manual keys of a laptop and an android application from which the commands will be transferred to the robots chassis using the Bluetooth communication module. The same will be functional using speech commands that will be passed onto the robot using the same procedure. The robot will also behave like a maze following bot and will continue to maneuver itself in a domain or an area that is filled with obstacles without collision into any of them. The obstacle avoidance or the maze following will he implemented using the Infrared Sensors. Finally a line following module is implemented along with the maze following module by integrating Charge Transfer Infrared sensors which is further combined with the path finding Pointbug algorithm in order to fine the optimal path from the source to the target by colliding with the obstacles and finding the minimum distance from the source to the target each time it meets with a collision with any of the obstacles. In addition to it the robot can also be controlled using the accelerometer functionalities. The entire project is developed in such a way that it is capable of traversing to the target location by avoiding all types of obstacles and moving on an optimized path and leading to significant results both with respect to time and energy and thereby implementing the latest technology in order to make the system to be controlled using Android, Bluetooth, speech and path finding algorithms to introduce intelligence into the control system to make suitable decisions at a particular instance of time so that the user is capable of reaching the target location without any type of interference or assistance from additional aids.

关键词： BOEbot bug algorithm Charge Transfer Infrared sensors Google voice to text Speech Recognition

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Sensor-based navigation of a car-like robot based on bug family algorithms

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2013年第C6期227卷 1224-1241页

作者： Kim, Dong-Hyung Shin, Kyoosik Han, Chang-Soo Lee, Ji Yeong Hanyang Univ Dept Mech Engn Gyeonggi Do South Korea

This article presents a sensor-based navigation algorithm for 3-degree-of-freedom car-like robots with a nonholonomic constraint. Similar to the classical bug family algorithms, the proposed algorithm enables the car-like robot to navigate in a completely unknown environment by only using range sensor information. The car-like robot uses the local range sensor view to determine the local path so that it moves toward the goal. To guarantee that the car-like robot can approach the goal, the two modes of motion are repeated, termed as motion-to-goal and wall-following. The motion-to-goal behavior lets the robot directly move toward the goal and the wall-following behavior makes the car-like robot circumnavigate the obstacle boundary until it meets the leaving condition. For each behavior, the nonholonomic motion for the car-like robot is planned in terms of the turning radius at each step. The proposed algorithm is implemented with a real robot and the experimental results show the performance of the proposed algorithm.

关键词： Autonomous navigation car-like robot bug algorithm nonholonomic constraint pure pursuit

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Performance comparison of bug navigation algorithms

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2007年第1期50卷 73-84页

作者： Ng, James Braeunl, Thomas Univ Western Australia EECE M01835 Stirling Hwy Perth WA 6009 Australia

The bug algorithm family are well-known robot navigation algorithms with proven termination conditions for unknown environments. Eleven variations of bug algorithm have been implemented and compared against each other on the EyeSim simulation platform. This paper discusses their relative performance for a number of different environment types as well as practical implementation issues.

关键词： mobile robot navigation algorithm bug algorithm performance comparison

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Fast Obstacle Detection Using 3D-to-2D LiDAR Point Cloud Segmentation for Collision-free Path Planning

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SENSORS AND MATERIALS 2020年第7期32卷 2365-2374页

作者： Lin, Chien-Chou Mao, Wei-Lung Chang, Teng-Wen Chang, Chuan-Yu Abdullah, Salah Sohaib Saleh Natl Yunlin Univ Sci & Technol Dept Comp Sci & Informat Engn 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Natl Yunlin Univ Sci & Technol Intelligence Recognit Ind Serv Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Natl Yunlin Univ Sci & Technol Dept Elect Engn 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Natl Yunlin Univ Sci & Technol Dept Digital Media Design 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan

Whereas many existing computer vision algorithms based on color images work well in robot navigation, most of them are sensitive to illumination and the reflectance of objects. Furthermore, according to the Oren-Nayar reflectance model, the reflectance depends on the material and surface of objects. Therefore, different sensors, passive sensors and active sensors, arc used simultaneously to scan objects of different materials. In this paper, an integrated sensor system, including light detection and ranging (Li DA R), global positioning system (GPS), gyroscopes (Gyro), and a camera, is proposed for an autonomous vehicle. The GPS and Gyros arc used for locating the robot position and identifying its orientation, which are used for global path planning to move toward a goal. The camera is used for remote video monitoring. LiDAR is used to capture the point clouds of the current environment for use in planning the local path. In this paper, a fast segmentation method is proposed for obstacle detection. The proposed method includes ground point removal, region of interest (ROI) detection. 3D -to -2D projection, and clustering by grids. The purpose of ROI detection is to determine whether the points are candidate obstacle points. The experimental results show that the proposed segmentation method can reduce the size of the point cloud and computation complexity significantly. The integrated multisensor system is expected to be practically used in the field.

关键词： LiDAR obstacle detection bug algorithm collision-free path planning point cloud segmentation

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Vectorization path planning for autonomous mobile agent in unknown environment

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NEURAL COMPUTING & APPLICATIONS 2013年第7-8期23卷 2129-2135页

作者： Xu, Qi-Lei Tang, Gong-You Ocean Univ China Coll Informat Sci & Engn Qingdao 266100 Peoples R China

This paper presents a novel real-time path planning algorithm, called Insertbug, for an autonomous mobile agent in completely unknown environment. By using the algorithm, all the planned paths are described and stored by vectors. The algorithm combines range sensor data with safety radius to determine the blocking obstacles and calculate the shortest path by choosing the intermediate points. When there is obstacle blocking the current path, the intermediate points will be calculated, and the planned path will be regenerated by inserting the intermediate points. The local optimum avoidance strategy is also considered in this algorithm by specifying a fixed direction. The agent will return to the optimal direction after running out of the local optimum. Different simulation parameters are taken to show the advantages of this algorithm. Moreover, the performance of this algorithm has also been evaluated by comparing with another usual method via simulations. The results show that the safety performance and time requirements of this algorithm are significant superior to the algorithm contrasted with.

关键词： Unknown environment Path planning Vectorization path bug algorithm

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Cognitive response navigation algorithm for mobile robots using biological antennas

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ROBOTICA 2014年第5期32卷 743-756页

作者： Jiang, Jiliang Tu, Dawei Xu, Shuo Zhao, Qijie Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Shanghai Univ Shanghai Key Lab Mfg Automat & Robot Shanghai 200072 Peoples R China

We present Biobug, a bionic cognitive response navigation algorithm for mobile robots based on neuroethology principles. It includes a biological antenna model for environment perception and an improved bug algorithm for motion planning and control. The biological antenna model delineates the interested sensing areas, and thus decreases the computational burden. Then, this obtained environment stimulation is responded to generate the corresponding walking behavior according to Biobug. Simulations and experiments have been carried out in different conditions of obstacle density and boundary shape through algorithm comparisons. Compared with the competitors, Biobug is characterized by not only a smaller path length, but also shorter time for obstacle escape. The results demonstrate the practicality, environment robustness, and obstacle avoidance efficiency of the algorithm.

关键词： bug algorithm Autonomous navigation Mobile robot Biological antenna Cognition Bionics

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Maximum clearance rapid motion planning algorithm

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ROBOTICA 2018年第6期36卷 882-903页

作者： Paliwal, Shubham Singh Kala, Rahul Indian Inst Informat Technol Robot & Artificial Intelligence Lab Allahabad Uttar Pradesh India

This paper proposes a new path-planning algorithm which is close to the family of bug algorithms. Path planning is one of the challenging problems in the area of service robotics. In practical applications, traditional methods have some limitations with respect to cost, efficiency, security, flexibility, portability, etc. Our proposed algorithm offers a computationally inexpensive goal-oriented strategy by following a smooth and short trajectory. The paper also presents comparisons with other algorithms. In addition, the paper also presents a test bed which is created to test the algorithm. We have used a two-wheeled differential drive robot for the navigation and only a single camera is used as a feedback sensor. Using an extended Kalman filter, we localize the robot efficiently in the map. Furthermore, we compare the actual path, predicted path and planned path to check the effectiveness of the control system.

关键词： Path planning bug algorithm Extended Kalman filter Homography Localization PID controller

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APF-bug-BASED INTELLIGENT PATH PLANNING FOR AUTONOMOUS VEHICLE WITH HIGH PRECISION IN COMPLEX ENVIRONMENT

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INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION 2023年第4期38卷 277-283页

作者： Sun, Lingyu Fu, Zhumu Tao, Fazhan Si, Pengju Song, Shuzhong Sun, Chang Henan Univ Sci & Technol Coll Informat Engn Luoyang Henan Peoples R China Henan Univ Sci & Technol Henan Key Lab Robot & Intelligent Syst Luoyang Henan Peoples R China Longmen Lab Luoyang Henan Peoples R China

With the increasing number of vehicles, driving environment is becoming increasingly complex and dynamic, which makes the driving of autonomous vehicle more difficult. In order to improve the safety of vehicle autonomous driving, in this paper, an improved artificial potential field (APF) path-planning algorithm for complex traffic environment with various obstacles is proposed. Considering the influence of vehicle physical characteristics on obstacle avoidance path, the repulsive potential field function of APF is improved. Then, aiming at the problem that traditional APF algorithm is easily fell into local extremum, a bug algorithm is introduced to ensure global performance of the proposed algorithm. Finally, feasibility and robustness of the proposed hybrid planning algorithm are validated by conducting several simulation investigations in a typical scenario.

关键词： Autonomous vehicle artificial potential field bug algorithm path planning obstacle avoidance

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Application of bug navigation algorithms for large-scale agent-based evacuation modeling to support decision making

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FIRE SAFETY JOURNAL 2021年 122卷 103322-103322页

作者： Haghpanah, Fardad Schafer, Benjamin W. Castro, Sebastian Johns Hopkins Univ Dept Civil & Syst Engn 3400 N Charles St Baltimore MD 21218 USA Natl Res Ctr Integrated Nat Disaster Management C Av Vicuna Mackenna 4860 Santiago 7820436 Chile

The global growth of urbanization has caused an increase of wildfires that devastate communities at wildlandurban interfaces. Agent-based evacuation simulation can be a powerful tool for emergency decision-makers to estimate evacuation times during rapidly propagating wildfires. However, as these models increase in size and complexity for urban areas, computation costs rise significantly, making these models less suitable for emergency situations. Although advances in high-performance computing have partially addressed the long execution time associated with large-scale models, the overall computation costs are still high considering the required infrastructure and technical knowledge. Alternatively, we can simplify certain components of the models such that accuracy will not be compromised greatly while computation speed is increased significantly. The authors suggest using the bug navigation algorithms, popular in the field of robotics, for the navigation of pedestrians. In the interest of finding the best candidate bug algorithm, a performance evaluation framework is also introduced. To demonstrate applicability, the evacuation of the city of Iquique, Chile, is simulated using the proposed approach. The results show that the proposed model is successful in estimating the evacuee arrival times, while execution time is reduced by orders of magnitude without a need for powerful processing resources.

关键词： Evacuation bug algorithm Navigation Agent-based modeling

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