A Robotic Software Framework for Autonomous Navigation in Unknown Environment

2021 ◽  
Author(s):  
Mir Md Sajid Sarwar ◽  
Rajeshwar Yadav ◽  
Sudip Samanta ◽  
Rajarshi Ray ◽  
Raju Halder ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Software Framework ◽  
Unknown Environment ◽  
Robotic Software

An Integrated Algorithm for Autonomous Navigation of a Mobile Robot in an Unknown Environment

2008 ◽  
Vol 12 (4) ◽  
pp. 328-335 ◽  
Author(s):  
Lee Gim Hee ◽  
◽  
Marcelo H. Ang Jr. ◽  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Hybrid Method ◽  
Autonomous Navigation ◽  
Prior Information ◽  
Optimal Path ◽  
Unknown Environment ◽  
Global Path Planning ◽  
Local Navigation ◽  
Navigation Algorithms

Global path planning algorithms are good in planning an optimal path in a known environment, but would fail in an unknown environment and when reacting to dynamic and unforeseen obstacles. Conversely, local navigation algorithms perform well in reacting to dynamic and unforeseen obstacles but are susceptible to local minima failures. A hybrid integration of both the global path planning and local navigation algorithms would allow a mobile robot to find an optimal path and react to any dynamic and unforeseen obstacles during an operation. However, the hybrid method requires the robot to possess full or partial prior information of the environment for path planning and would fail in a totally unknown environment. The integrated algorithm proposed and implemented in this paper incorporates an autonomous exploration technique into the hybrid method. The algorithm gives a mobile robot the ability to plan an optimal path and does online collision avoidance in a totally unknown environment.

scholarly journals Autonomous navigation in unknown environment using sliding mode SLAM and genetic algorithm

2021 ◽  
Author(s):  
Salvador Ortiz ◽  
Wen Yu
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Sliding Mode Control ◽  
Autonomous Navigation ◽  
Sliding Mode ◽  
Simultaneous Localization And Mapping ◽  
Planning Method ◽  
Unknown Environment ◽  
Localization And Mapping ◽  
Bounded Uncertainties

In this paper, sliding mode control is combined with the classical simultaneous localization and mapping (SLAM) method. This combination can overcome the problem of bounded uncertainties in SLAM. With the help of genetic algorithm, our novel path planning method shows many advantages compared with other popular methods.

Autonomous navigation for a holonomic drive robot in an unknown environment using a depth camera

2020 ◽  
Author(s):  
Jesus Aleman ◽  
Hector Samuel Monjardin Hernandez ◽  
Ulises Orozco-Rosas ◽  
Kenia Picos
Keyword(s):  
Autonomous Navigation ◽  
Depth Camera ◽  
Unknown Environment

scholarly journals A Review: Simultaneous Localization and Mapping in Application to Autonomous Robot

2018 ◽  
Author(s):  
Olusanya Agunbiade ◽  
Tranos Zuva
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Simultaneous Localization And Mapping ◽  
Research Direction ◽  
Autonomous Robot ◽  
Unknown Environment ◽  
Computational Problem ◽  
Localization And Mapping ◽  
Open Issues

The important characteristic that could assist in autonomous navigation is the ability of a mobile robot to concurrently construct a map for an unknown environment and localize itself within the same environment. This computational problem is known as Simultaneous Localization and Mapping (SLAM). In literature, researchers have studied this approach extensively and have proposed a lot of improvement towards it. More so, we are experiencing a steady transition of this technology to industries. However, there are still setbacks limiting the full acceptance of this technology even though the research had been conducted over the last 30 years. Thus, to determine the problems facing SLAM, this paper conducted a review on various foundation and recent SLAM algorithms. Challenges and open issues alongside the research direction for this area were discussed. However, towards addressing the problem discussed, a novel SLAM technique will be proposed.

Indoor Autonomous Navigation Technology Research Based on Lidar for Quad-Copter Aerial Robot

2014 ◽  
Vol 538 ◽  
pp. 371-374
Author(s):  
Zhi Jun Bai ◽  
Yang Feng Ji ◽  
Liao Ni Wu ◽  
Qi Lin
Keyword(s):  
Navigation System ◽  
Autonomous Navigation ◽  
Simultaneous Localization And Mapping ◽  
Technology Research ◽  
Unknown Environment ◽  
Monocular Camera ◽  
Localization And Mapping ◽  
Aerial Robot ◽  
Test Result ◽  
Autonomous Navigation System

An indoor autonomous navigation system without GPS has been developed, based on the platform of quad-copter, which may fulfill the task of searching, identifying and entering the target room in a building with multi-rooms corridor. A pose sensor was utilized to stabilize the aircraft. The SLAM (Simultaneous Localization and Mapping) and plan route in unknown environment have been created by a 2D lidar. A calibrated monocular camera has been used to recognize different marks to make sure the vehicle to enter the target room. The test result showed that the indoor autonomous navigation technology based on lidar for quad-copter aerial robot is feasible and successful.

Study on Intelligent Obstacle Avoidance and Autonomous Navigation

2012 ◽  
Vol 182-183 ◽  
pp. 1333-1337
Author(s):  
Meng Long Cao ◽  
Li Na Sun
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Navigation ◽  
Fuzzy Reasoning ◽  
Sensor Data ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Unknown Environment

Precise navigation and localization of the autonomous rover in unknown environment is important both for its own safety as well as for its ability to accomplish engineering and scientific objectives. In order to navigation autonomously the rover should have the ability of apperceiving the environment and avoiding the obstacles. Laser range finder is used to rebuild the environment and fuzzy reasoning method is used to avoid obstacles. Most importantly the rover process the sensor data to produce an estimate of its position while concurrently building a map of the environment. The improved filter algorithm is proposed to make the method feasible.

scholarly journals Efficient and High Path Quality Autonomous Exploration and Trajectory Planning of UAV in an Unknown Environment

2021 ◽  
Vol 10 (10) ◽  
pp. 631
Author(s):  
Leyang Zhao ◽  
Li Yan ◽  
Xiao Hu ◽  
Jinbiao Yuan ◽  
Zhenbao Liu
Keyword(s):  
Path Planning ◽  
Autonomous Navigation ◽  
Research Direction ◽  
Step Size ◽  
Autonomous Exploration ◽  
Autonomous Flight ◽  
Main Research ◽  
Adaptive Weights ◽  
Unknown Environment ◽  
Difference Polynomial

The ability of an autonomous Unmanned Aerial Vehicle (UAV) in an unknown environment is a prerequisite for its execution of complex tasks and is the main research direction in related fields. The autonomous navigation of UAVs in unknown environments requires solving the problem of autonomous exploration of the surrounding environment and path planning, which determines whether the drones can complete mission-based flights safely and efficiently. Existing UAV autonomous flight systems hardly perform well in terms of efficient exploration and flight trajectory quality. This paper establishes an integrated solution for autonomous exploration and path planning. In terms of autonomous exploration, frontier-based and sampling-based exploration strategies are integrated to achieve fast and effective exploration performance. In the study of path planning in complex environments, an advanced Rapidly Exploring Random Tree (RRT) algorithm combining the adaptive weights and dynamic step size is proposed, which effectively solves the problem of balancing flight time and trajectory quality. Then, this paper uses the Hermite difference polynomial to optimization the trajectory generated by the RRT algorithm. We named proposed UAV autonomous flight system as Frontier and Sampling-based Exploration and Advanced RRT Planner system (FSEPlanner). Simulation performs in both apartment and maze environment, and results show that the proposed FSEPlanner algorithm achieves greatly improved time consumption and path distances, and the smoothed path is more in line with the actual flight needs of a UAV.

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