Motion Planning for a Chain of Mobile Robots Using A and Potential Field
Traditionally, motion planning involved navigating one robot from source to goal for accomplishing a task. Now, tasks mostly require movement of a team of robots to the goal site, requiring a chain of robots to reach the desired goal. While numerous efforts are made in the literature for solving the...
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| Published in | Robotics (Basel) Vol. 7; no. 2; p. 20 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Basel
MDPI AG
01.06.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2218-6581 2218-6581 |
| DOI | 10.3390/robotics7020020 |
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| Abstract | Traditionally, motion planning involved navigating one robot from source to goal for accomplishing a task. Now, tasks mostly require movement of a team of robots to the goal site, requiring a chain of robots to reach the desired goal. While numerous efforts are made in the literature for solving the problems of motion planning of a single robot and collective robot navigation in isolation, this paper fuses the two paradigms to let a chain of robot navigate. Further, this paper uses SLAM to first make a static map using a high-end robot, over which the physical low-sensing robots run. Deliberative Planning uses A* algorithm to plan the path. Reactive planning uses the Potential Field Approach to avoid obstacles and stay as close to the initial path planned as possible. These two algorithms are then merged to provide an algorithm that allows the robot to reach its goal via the shortest path possible while avoiding obstacles. The algorithm is further extended to multiple robots so that one robot is followed by the next robot and so on, thus forming a chain. In order to maintain the robots in a chain form, the Elastic Strip model is used. The algorithm proposed successfully executes the above stated when tested on Amigobot robots in an office environment using a map made by the Pioneer LX robot. The proposed algorithm works well for moving a group of robots in a chain in a mapped environment. |
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| AbstractList | Traditionally, motion planning involved navigating one robot from source to goal for accomplishing a task. Now, tasks mostly require movement of a team of robots to the goal site, requiring a chain of robots to reach the desired goal. While numerous efforts are made in the literature for solving the problems of motion planning of a single robot and collective robot navigation in isolation, this paper fuses the two paradigms to let a chain of robot navigate. Further, this paper uses SLAM to first make a static map using a high-end robot, over which the physical low-sensing robots run. Deliberative Planning uses A* algorithm to plan the path. Reactive planning uses the Potential Field Approach to avoid obstacles and stay as close to the initial path planned as possible. These two algorithms are then merged to provide an algorithm that allows the robot to reach its goal via the shortest path possible while avoiding obstacles. The algorithm is further extended to multiple robots so that one robot is followed by the next robot and so on, thus forming a chain. In order to maintain the robots in a chain form, the Elastic Strip model is used. The algorithm proposed successfully executes the above stated when tested on Amigobot robots in an office environment using a map made by the Pioneer LX robot. The proposed algorithm works well for moving a group of robots in a chain in a mapped environment. |
| Author | Kala, Rahul Apoorva Gautam, Rahul |
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| References | Hamaguchi (ref_18) 2013; 2013 Shackleton (ref_21) 2013; 2 Khatib (ref_3) 1986; 5 Hart (ref_7) 1968; 4 ref_14 Kala (ref_6) 2010; 33 ref_13 ref_24 ref_12 ref_22 ref_10 ref_20 ref_1 ref_2 ref_19 ref_16 Guruji (ref_8) 2016; 23 Kavralu (ref_11) 1996; 12 ref_15 Elfes (ref_23) 1987; 3 ref_9 Chen (ref_17) 2017; 2017 ref_5 ref_4 |
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| SubjectTerms | Algorithms Automation Barriers Chain mobility Chains Collaboration Fuses Heuristic International conferences Motion planning Multiple robots Planning Robot dynamics Robotics Robots Sensors Shortest-path problems |
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| Title | Motion Planning for a Chain of Mobile Robots Using A and Potential Field |
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