Stereo camera-based intelligent mobile robot system for path planning and navigation

2005 ◽  
Author(s):  
Jung-Hwan Ko ◽  
Jae-Hun Jang ◽  
Eun-Soo Kim
2005 ◽  
Author(s):  
Jung-Hwan Ko ◽  
Dong-Choon Hwang ◽  
Yong-Woo Jung ◽  
Eun-Soo Kim

Robotica ◽  
2019 ◽  
Vol 38 (3) ◽  
pp. 493-511 ◽  
Author(s):  
Yang Chen ◽  
Shiwen Ren ◽  
Zhihuan Chen ◽  
Mengqing Chen ◽  
Huaiyu Wu

SummaryThis paper considers the path planning problem for deployment and collection of a marsupial vehicle system which consists of a ground mobile robot and two aerial flying robots. The ground mobile robot, usually unmanned ground vehicle (UGV), as a carrier, is able to deploy and harvest the aerial flying robots, and each aerial flying robot, usually unmanned aerial vehicles (UAVs), takes off from and lands on the carrier. At the same time, owing to the limited duration in the air in one flight, UAVs should return to the ground mobile robot timely for its energy-saving and recharge. This work is motivated by cooperative search and reconnaissance missions in the field of heterogeneous robot system. Especially, some targets with given positions are assumed to be visited by any of the UAVs. For the cooperative path planning problem, this paper establishes a mathematical model to solve the path of two UAVs and UGV. Many real constraints including the maximum speed of two UAVs and UGV, the minimum charging time of two UAVs, the maximum hovering time of UAVs, and the dynamic constraints among UAVs and UGV are considered. The objective function is constructed by minimizing the time for completing the whole mission. Finally, the path planning problem of the robot system is transformed into a multi-constrained optimization problem, and then the particle swarm optimization algorithm is used to obtain the path planning results. Simulations and comparisons verify the feasibility and effectiveness of the proposed method.


2011 ◽  
Vol 16 (1) ◽  
pp. 5-9 ◽  
Author(s):  
Sheng-Ven Shiau ◽  
Kuo-Lan Su ◽  
Chun-Chieh Wang ◽  
Jr-Hung Guo

2012 ◽  
Vol 523-524 ◽  
pp. 895-900 ◽  
Author(s):  
Tohru Sasaki ◽  
Takayuki Ushimaru ◽  
Takahiro Yamatani ◽  
Yusuke Ikemoto ◽  
Haruki Obara

The stereo-camera method is used to measure the positions of robots. In taking the measurements it is important to precisely measure the distance between cameras and the relative posture of the cameras. Therefore, we developed a novel method for measuring a mobile robot's relative position and posture by photographing robots’ pivot turns. A mobile robot system was equipped with a camera and an identification marker that made it possible to measure position and posture with the stereo-camera method when the viewpoint changed freely. One robot photographs the pivot turns of another. As the latter turns, an identification marker on it is used to trace the movement onto an image. The turning robot’s position and posture is determined by the length and angle of the trace. This procedure makes it possible for each of the two robots to obtain their relative position and posture, making the measurement of the stereo-camera method precise. Measuring with a fixed stereo camera is impossible when there are obstacles in the environment and the object being measured moves over a wide range. However, this robot system was able to use the stereo-camera method to expand the measurement range.


2017 ◽  
Vol 5 (1) ◽  
pp. 198-205 ◽  
Author(s):  
V. Keerthana ◽  
C. Kiruthiga ◽  
P. Kiruthika ◽  
V. Sowmiya ◽  
R. Manikadan

The field of autonomous mobile robotics has recently gained many researchers’ interests. Due to the specific needs required by various applications of mobile robot systems, especially in navigation, designing a real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective of our project is applications based mobile robot systems, especially in navigation, designing real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective behind using the obstacle avoidance approach is to obtain a collision-free trajectory from the starting point to the target in monitoring environments. The ability of the robot to follow a path, detects obstacles, and navigates around them to avoid collision. It also shows that the robot has been successfully following very congested curves and has avoided any obstacle that emerged on its path. Motion planning that allows the robot to reach its target without colliding with any obstacles that may exist in its path. To avoid collision in the mobile robot environment, providing a path planning& line following approach. Line following, path planning, collision avoidance, back propagation, improved memory, detecting long distance obstacles. Cheap and economical than the former one. Also work with back propagation technique.


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