Optimal arrest and guidance of a moving prismatic object using multiagents

Robotica ◽  
2008 ◽  
Vol 26 (1) ◽  
pp. 41-53 ◽  
Author(s):  
Pankaj Sharma ◽  
Anupam Saxena ◽  
Ashish Dutta
Keyword(s):  
Point Contact ◽  
Object Boundary ◽  
Actual Object ◽  
Linear Path ◽  
Form Closure ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Path Planning Algorithm ◽  
Point Form ◽  
Multi Agents

SUMMARYGenetic algorithm is used to determine the optimal capture points for the multi agents required to grasp a moving generic prismatic object by arresting it in form closure. Thereafter, the agents approach their respective moving goals using a decentralized projective path planning algorithm. Post arrest, the object is guided along a desired linear path to a desired goal point. Form closure of the object is obtained using the concept of accessibility angle. A convex envelop is formed around the object, and the goal points on the object boundary are mapped onto the envelope. The robots approach the mapped goal points first, and then, converge on the actual object. This ensures that the agents reach the actual goal points almost simultaneously, and do not undergo looping at a local concave region. The object is assumed alive while being captured but is assumed compromised thereafter. Post arrest, robots alter their positions optimally around the object to transport it along a desired direction. Frictionless point contact between the object and a robot is assumed. The shape of the mobile robot is considered cylindrical such that it can only apply force along the outward radial direction. Simulation results are presented that illustrate the effectiveness of the proposed method.

Multi-Agent Form Closure Capture of a Generic 2D Polygonal Object Based on Projective Path Planning

2006 ◽  
Author(s):  
Pankaj Sharma ◽  
Anupam Saxena ◽  
Ashish Dutta
Keyword(s):  
Path Planning ◽  
Contact Point ◽  
Point Contact ◽  
Object Boundary ◽  
Actual Object ◽  
Contact Points ◽  
Correct Orientation ◽  
Novel Approach ◽  
Form Closure ◽  
Multi Agent

The study of multi-agent capture and manipulation of an object has been an area of active interest for many researchers. This paper presents a novel approach using Genetic Algorithm to determine the optimal contact points and the total number of agents (mobile robots) required to capture a stationary generic 2D polygonal object. After the goal points are determined the agents then reach their respective goals using a decentralized projective path planning algorithm. Form closure of the object is obtained using the concept of accessibility angle. The object boundary is first expanded and the robots reach the expanded object goal points and then converge on the actual object. This ensures that the agents reach the actual goal points at the same time and have the correct orientation. Frictionless point contact between the object and robots is assumed. The shape of the robot is considered a circle such that it can only apply force in outward radial direction from its center and along the normal to the object boundary at the contact point. Simulations results are presented that prove the effectiveness of the proposed method.

Autonomous Collision Imminent Steering Maneuver in Presence of Surrounding Obstacles

2016 ◽  
Author(s):  
Rouhollah Jafari ◽  
Shuqing Zeng ◽  
Nikolai Moshchuk
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Geometric Method ◽  
Target Vehicle ◽  
Virtual Target ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Collision Avoidance System ◽  
Path Planning Algorithm

In this paper, a collision avoidance system is proposed to steer away from a leading target vehicle and other surrounding obstacles. A virtual target lane is generated based on an object map resulted from perception module. The virtual target lane is used by a path planning algorithm for an evasive steering maneuver. A geometric method which is computationally fast for real-time implementations is employed. The algorithm is tested in real-time and the simulation results suggest the effectiveness of the system in avoiding collision with not only the leading target vehicle but also other surrounding obstacles.

scholarly journals Hybrid Partition-Based Patrolling Scheme for Maritime Area Patrol with Multiple Cooperative Unmanned Surface Vehicles

2020 ◽  
Vol 8 (11) ◽  
pp. 936
Author(s):  
Jiajia Xie ◽  
Rui Zhou ◽  
Jun Luo ◽  
Yan Peng ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Forest Fires ◽  
Low Cost ◽  
Search And Rescue ◽  
Unmanned Surface Vehicles ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Path Planning Algorithm ◽  
The Given ◽  
Maritime Environment ◽  
Multi Robot

Multi-robot cooperative patrolling systems have been extensively employed in the civilian and military fields, including monitoring forest fires, marine search-and-rescue, and area patrol. Multi-robot area patrol problems refer to the activity that a team of robots works cooperatively and regularly to visit the key targets in the given area for security. Following consideration of the low cost and high safety of unmanned surface vehicles (USV), a team of USVs is organized to perform area patrol in a sophisticated maritime environment. In this paper, we establish a mathematical model considering the characteristics of the cooperative patrol task and the limited conditions of USVs. A hybrid partition-based patrolling scheme is proposed for a multi-USV system to visit targets with different importance levels in a maritime area. Firstly, a centralized area partition algorithm is utilized to partition the patrolling area according to the number of USVs. Secondly, a distributed path planning algorithm is applied to planning the patrolling path for each USV to visit the targets in a maritime environment to minimize the length of the patrolling path for the USV team. Finally, comparative experiments between the proposed scheme and other methods are carried out to validate the performance of the hybrid partition-based patrolling scheme. Simulation results and experimental analysis show the efficiency of the proposed hybrid partition-based patrolling scheme compared to several previous patrolling algorithms.

A Novel Path Planning Algorithm for Autonomous Underwater Vehicle

2013 ◽  
Vol 446-447 ◽  
pp. 1271-1278
Author(s):  
Bo Yin ◽  
Bing Liu ◽  
Jing Cao
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Moving Simulation ◽  
Path Planning Algorithm

A path planning algorithm based on sector scanning for AUV was proposed in this paper. By reducing the frequency of the calculation of the path planning, this method solved the problem that AUV can not respond to the frequent control instructions of path planning because of AUV’s poor flexibility. Meanwhile, by making the path more clear and reliable, the algorithm improved the operability of responding to the path planning results and operating the controlling of AUV’s moving. Simulation results show that this method is feasible and efficient.

scholarly journals An Intelligent Path Selection Algorithm Based on Deep Reinforcement Learning

2021 ◽  
Vol 2078 (1) ◽  
pp. 012023
Author(s):  
Mengchen Sun
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Path Selection ◽  
Learning Ability ◽  
Continuous Learning ◽  
Selection Algorithm ◽  
Planning Algorithm ◽  
Intelligent Devices ◽  
Simulation Results ◽  
Path Planning Algorithm

Abstract Path selection is the most important algorithm in intelligent devices such as robots. At present, the traditional path-planning algorithm has achieved some results, but it lacks the ability of environmental perception and continuous learning. In order to solve the above problems, this paper proposes an intelligent path selection algorithm based on deep reinforcement learning, which uses the learning ability of deep learning and the decision-making ability of reinforcement learning to realize the autonomous path planning of robots and other equipment. Simulation results show that the proposed algorithm has faster convergence, efficiency and accuracy.

Radom Intermediate Points Based Path Planning in Unknown Environment

2013 ◽  
Vol 325-326 ◽  
pp. 1688-1691
Author(s):  
Qi Lei Xu ◽  
Gong You Tang ◽  
Hai Lin Liu ◽  
Shao Ting Ge ◽  
Xue Yang
Keyword(s):  
Path Planning ◽  
Mobile Agent ◽  
Rotation Angle ◽  
Sensor Data ◽  
Unknown Environment ◽  
Current Path ◽  
Movement Distance ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Path Planning Algorithm

This paper presents RandomBug, a novel real-time path planning algorithm, for an autonomous mobile agent in completely unknown environment. According to this algorithm, all the planned paths are described and stored in the form of vectors. When the agent moves along the planned paths, it only considers the rotation angle and the movement distance in a single direction. The algorithm combines range sensor data with a safety radius to determine the blocking obstacles and calculate the shorter path by choosing the random intermediate points. When there is obstacle blocking in the current path, the intermediate points will be calculated randomly and the planned path will be regenerated by inserting the selected random intermediate points. Simulation results are given to show the effectiveness of the proposed algorithm.

scholarly journals RandomBug: Novel Path Planning Algorithm in Unknown Environment

2014 ◽  
Vol 8 (1) ◽  
pp. 252-257 ◽  
Author(s):  
Qi-lei Xu
Keyword(s):  
Path Planning ◽  
Mobile Agent ◽  
Rotation Angle ◽  
Sensor Data ◽  
Unknown Environment ◽  
Current Path ◽  
Movement Distance ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Path Planning Algorithm

This paper presents a novel real-time path planning algorithm for an autonomous mobile agent in completely unknown environment. In this algorithm, all the planned paths are described and stored in the form of vectors in the algorithm. Only the rotation angle and the movement distance in a single direction are considered when the autonomous moves along the planned paths. The algorithm combines range sensor data with a safety radius, which determines the blocking obstacles and calculates a shorter path by choosing the random intermediate points. These random intermediate points are be generated when blocking obstacles exist in the current path. Then the optimal intermediate points are selected and inserted into the current path to regenerate a new planned path. Simulation results are shown that the proposed algorithm is effective.

scholarly journals A Bi-Level Probabilistic Path Planning Algorithm for Multiple Robots with Motion Uncertainty

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Jingchuan Wang ◽  
Ruochen Tai ◽  
Jingwen Xu
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Conflict Avoidance ◽  
System Efficiency ◽  
Multiple Robots ◽  
Time Performance ◽  
Planning Algorithm ◽  
Probabilistic Path Planning ◽  
Simulation Results ◽  
Path Planning Algorithm

For improving the system efficiency when there are motion uncertainties among robots in the warehouse environment, this paper proposes a bi-level probabilistic path planning algorithm. In the proposed algorithm, the map is partitioned into multiple interconnected districts and the architecture of proposed algorithm is composed of topology level and route level generating from above map: in the topology level, the order of passing districts is planned combined with the district crowdedness to achieve the district equilibrium and reduce the influence of robots under motion uncertainty. And in the route level, a MDP method combined with probability of motion uncertainty is proposed to plan path for all robots in each district separately. At the same time, the number of steps for each planning is dependent on the probability to decrease the number of planning. The conflict avoidance is proved, and optimization is discussed for the proposed algorithm. Simulation results show that the proposed algorithm achieves improved system efficiency and also has acceptable real-time performance.

scholarly journals Research on optimal path planning of indoor robot based on wireless sensor

2021 ◽  
Vol 2093 (1) ◽  
pp. 012009
Author(s):  
Shouwen Wang
Keyword(s):  
Path Planning ◽  
Wireless Sensors ◽  
Optimal Path ◽  
Wireless Sensor ◽  
Target Point ◽  
Optimal Path Planning ◽  
Work Tasks ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Path Planning Algorithm

Abstract Based on the work tasks and positioning characteristics of indoor robots, the environment is divided into grids, and wireless sensors are used to detect obstacles, and the density of obstacles in each grid is given. At the same time, the path planning algorithm is combined to realize the optimal path planning of indoor robot. The simulation results show that the wireless sensor network can realize the obstacle density detection, so that the robot can achieve fast optimal path planning and reach the target point.

Velocity-Regulated Path Planning Algorithm for Aerosol Printing Systems

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Bradley Thompson ◽  
Hwan-Sik Yoon
Keyword(s):  
Path Planning ◽  
Relative Velocity ◽  
Printed Electronics ◽  
Aerosol Printing ◽  
Planning Algorithm ◽  
Printing System ◽  
The Common ◽  
Simulation Results ◽  
Speed Fluctuations ◽  
Path Planning Algorithm

Aerosol printing is one of the common methods used in printed electronics. In this study, an improved path planning algorithm is developed for an aerosol printing system. The continuous aerosol stream provided by a printing nozzle requires a constant relative velocity between the printer head and substrate in order to evenly deposit materials. To ensure consistency, the proposed algorithm confines speed fluctuations by predetermining potential velocity errors and compensating with a novel scheme. The path planning algorithm can control motion of an XY stage for an arbitrary printing path and desired velocity while minimizing material waste. Linear segments with parabolic blends (LSPB) trajectory planning is used during printing, and minimum time trajectory (MTT) planning is used during printer transition. Simulation results demonstrate the algorithm's improved capability to maintain the desired velocity while minimizing print time.

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