A Rapid Recognition of Impassable Terrain for Mobile Robots with Low Cost Range Finder Based on Hypotheses Testing Theory

Gao, Yang; Wu, Xueyi; Liu, Yu; Li, Jian Ming; Liu, Jia Hao

doi:10.15837/ijccc.2017.6.2981

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…The design of 3-D sensors including NIPON Signal F6, IFM O3D200, Fotonic E70P, Microsoft Kinect, and ASUS Xtion Pro Live, have improved the autonomous performance of mobile robots [22]. The possibilities of using low-cost sensors for 3-D detection are also investigated using RADAR and learning techniques [23].…”

Section: Robot Perception Methods and Latest Developmentsmentioning

confidence: 99%

Recent developments in terrain identification, classification, parameter estimation for the navigation of autonomous robots

Nampoothiri

Sunny

et al. 2021

SN Appl. Sci.

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The work presents a review on ongoing researches in terrain-related challenges influencing the navigation of Autonomous Robots, specifically Unmanned Ground ones. The paper aims to highlight the recent developments in robot design and advanced computing techniques in terrain identification, classification, parameter estimation, and developing modern control strategies. The objective of our research is to familiarize the gaps and opportunities of the aforementioned areas to the researchers who are passionate to take up research in the field of autonomous robots. The paper brings recent works related to terrain strategies under a single platform focusing on the advancements in planetary rovers, rescue robots, military robots, agricultural robots, etc. Finally, this paper provides a comprehensive analysis of the related works which can bridge the AI techniques and advanced control strategies to improve navigation. The study focuses on various Deep Learning techniques and Fuzzy Logic Systems in detail. The work can be extended to develop new control schemes to improve multiple terrain navigation performance.

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Section: Robot Perception Methods and Latest Developmentsmentioning

confidence: 99%

Recent developments in terrain identification, classification, parameter estimation for the navigation of autonomous robots

Nampoothiri

Sunny

et al. 2021

SN Appl. Sci.

View full text Add to dashboard Cite

show abstract

“…It requires the robot process as far as possible not to deviate from the specified path, unless the obstacles encountered when the movement had to bypass the walk. But after avoiding the obstacle, the mobile robot must return to the original path until it reaches the destination [3,8,15,18,21].…”

Section: Introductionmentioning

confidence: 99%

A New Hybrid Method in Global Dynamic Path Planning of Mobile Robot

Song

Gao²,

Chen³

et al. 2018

INT J COMPUT COMMUN

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Path planning and real-time obstacle avoidance is the key technologies of mobile robot intelligence. But the efficiency of the global path planning is not very high. It is not easy to avoid obstacles in real time. Aiming at these shortcomings it is proposed that a global dynamic path planning method based on improved A* algorithm and dynamic window method. At first the improved A* algorithm is put forward based on the traditional A* algorithm in the paper. Its optimized heuristic search function is designed. They can be eliminated that the redundant path points and unnecessary turning points. Simulation experiment 1 results show that the planned path length is reduced greatly. And the path transition points are less, too. And then it is focused on the global dynamic path planning of fusion improved A* Algorithm and Dynamic Window Method. The evaluation function is constructed taking into account the global optimal path. The real time dynamic path is planning. On the basis of ensuring the optimal global optimization of the planning path, it is improved that the smoothness of the planning path and the local real-time obstacle avoidance ability. The simulation experiments results show that the fusion algorithm is not only the shorter length, but also the smoother path compared the traditional path planning algorithms with the fusion algorithm in the paper. It is more fit to the dynamics of the robot control. And when a dynamic obstacle is added, the new path can be gained. The barrier can be bypass and the robot is to reach the target point. It can be guaranteed the global optimality of the path. Finally the Turtlebot mobile robot was used to experiment. The experimental results show that the global optimality of the proposed path can be guaranteed by the fusion algorithm. And the planned global path is smoother. When the random dynamic obstacle occurs in the experiment, the robot can be real-time dynamic obstacle avoidance. It can re-plan the path. It can bypass the random obstacle to reach the original target point. The outputting control parameters are more conducive to the robot’s automatic control. The fusion method is used for global dynamic path planning of mobile robots in this paper. In summary the experimental results show that the method is good efficiency and real-time performance. It has great reference value for the dynamic path planning application of mobile robot.

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A Rapid Recognition of Impassable Terrain for Mobile Robots with Low Cost Range Finder Based on Hypotheses Testing Theory

Cited by 2 publications

References 11 publications

Recent developments in terrain identification, classification, parameter estimation for the navigation of autonomous robots

Recent developments in terrain identification, classification, parameter estimation for the navigation of autonomous robots

A New Hybrid Method in Global Dynamic Path Planning of Mobile Robot

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