SLAM using AD* Algorithm with Absolute Odometry

被引:1
|
作者
Hanagi, Rohan Ravindra [1 ]
Gurav, Omkar Shivling [1 ]
Khandekar, Shridhar A. [1 ]
机构
[1] MIT Acad Engn, Sch Elect Engn, Pune, Maharashtra, India
来源
2021 6TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT) | 2021年
关键词
SLAM; AD* algorithm; Mobile Robot; localization; mapping; Holonomic motion; Absolute odometry; occupancy grid; Agent;
D O I
10.1109/I2CT51068.2021.9418118
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The use of mobile robots is continuously increasing in Industrial applications such as assembly line automation, warehouse robots, inspection in power lines in smart grids etc. Localization and mapping are the key technologies of mobile robots and Simultaneous Localization and Mapping (SLAM) is considered as an essential basis for this. SLAM is usually resource intensive and also requires high fidelity sensors in order to navigate an environment effectively. Hector SLAM continuously uses all nearby obstacles and objects in order to determine the location of the robot. This is resource intensive as the agent keeps a track of all the objects in its proximity. To cope with this problem, this paper proposes Anytime D* algorithm along with absolute odometry we eliminate the factor of continuously monitoring the environment W.R.T to the robot/agent. The localization of the agent is done by using reverse kinematics. This allows for the use of low fidelity sensors such as Infrared sensors as well as Ultrasonic sensors. This algorithm creates an occupancy grid in real time as the agent moves through the environment with a goal to goal controller.
引用
收藏
页数:4
相关论文
共 50 条
  • [41] Drift-Free Visual SLAM Using Digital Twins
    Merat, Roxane
    Cioffi, Giovanni
    Bauersfeld, Leonard
    Scaramuzza, Davide
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2025, 10 (02): : 1633 - 1640
  • [42] CMax-SLAM: Event-Based Rotational-Motion Bundle Adjustment and SLAM System Using Contrast Maximization
    Guo, Shuang
    Gallego, Guillermo
    IEEE TRANSACTIONS ON ROBOTICS, 2024, 40 : 2442 - 2461
  • [43] B-SLAM-SIM: A Novel Approach to Evaluate the Fusion of Visual SLAM and GPS by Example of Direct Sparse Odometry and Blender
    Kalisz, Adam
    Particke, Florian
    Penk, Dominik
    Hiller, Markus
    Thielecke, Joern
    PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 5, 2019, : 816 - 823
  • [44] Improving odometry using a controlled point laser
    Epton, Tom
    Hoover, Adam
    AUTONOMOUS ROBOTS, 2012, 32 (02) : 165 - 172
  • [45] GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
    Kiss-Illes, Daniel
    Barrado, Cristina
    Salami, Esther
    SENSORS, 2019, 19 (22)
  • [46] A novel algorithm for SLAM in dynamic environments using landscape theory of aggregation
    华承昊
    窦丽华
    方浩
    付浩
    Journal of Central South University, 2016, 23 (10) : 2587 - 2594
  • [47] A novel algorithm for SLAM in dynamic environments using landscape theory of aggregation
    Hua Cheng-hao
    Dou Li-hua
    Fang Hao
    Fu Hao
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2016, 23 (10) : 2587 - 2594
  • [48] A Multibeam-Based SLAM Algorithm for Iceberg Mapping Using AUVs
    Norgren, Petter
    Skjetne, Roger
    IEEE ACCESS, 2018, 6 : 26318 - 26337
  • [49] A novel algorithm for SLAM in dynamic environments using landscape theory of aggregation
    Cheng-hao Hua
    Li-hua Dou
    Hao Fang
    Hao Fu
    Journal of Central South University, 2016, 23 : 2587 - 2594
  • [50] Co-Planar Parametrization for Stereo-SLAM and Visual-Inertial Odometry
    Li, Xin
    Li, Yanyan
    Ornek, Evin Pnar
    Lin, Jinlong
    Tombari, Federico
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2020, 5 (04): : 6972 - 6979