Orientation Planning for Multi-Agents With Discrete-Step Locomotion and Multiple Goals

Author(s):  
Keerthi Sagar ◽  
Dimiter Zlatanov ◽  
Matteo Zoppi ◽  
Cristiano Nattero ◽  
Sreekumar Muthuswamy

The paper addresses the coordinated path planning of mobile agents with multiple goal positions and orientations in a plane. The targeted multi-robot system uses discrete locomotion ensuring uncertainty-free localization and mapping as well as simple and robust control. It is suitable for material-handling, reconfigurable-fixturing, and mobile-manipulation tasks in a flexible-manufacturing environment. Using its three leg, and matching pin-socket couplings with the base surface, each agent either stands fixed or strides along via “Swing and Dock” (SaD) locomotion. Each mounting pin can serve both as a connecting-locking device and as a pivot of a planar rotation. Previous work offered planning solutions only for the agents’ positions. In reality, the orientation in which the agent arrives at the goal is very important because neither robot workspaces nor workcell geometries have axial symmetry. Herein, we provide for the required orientational planning by labelling the agent’s legs to keep track of its rotation. Integer Linear Programming (ILP) is used to model the path planning problem in the so augmented configuration space. The mathematical formulations are implemented and tested using a GUROBI solver. Computational results display the effectiveness of the approach.

2018 ◽  
Vol 160 ◽  
pp. 06004
Author(s):  
Zi-Qiang Wang ◽  
He-Gen Xu ◽  
You-Wen Wan

In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM) to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM) for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.


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.


Author(s):  
Keerthi Sagar ◽  
Dimiter Zlatanov ◽  
Matteo Zoppi ◽  
Cristiano Nattero ◽  
Sreekumar Muthuswamy

The paper introduces a new, intrinsically discrete, path planning and collision-avoidance problem, with multiple robots and multiple goals. The issue arises in the operation of the novel Swing and Dock (SaD) locomotion for a material handling system. Its agents traverse a base grid by sequences of rotations (swings) around fixed pins. Each agent must visit an array of goal positions in minimal time while avoiding collisions. The corresponding off-line path-planning problem is NP-hard. We model the system by an extended temporal graph and introduce two integer linear programming (ILP) formulations for the minimization of the makespan, with decision variables on the nodes and the edges, respectively. Both optimizations are constrained and favor idling over detours to reduce mechanical wear. The ILP formulations, tailored to the SaD system, are general enough to be applicable for many other single- and multi-agent problems over discretized networks. We have implemented the ILPs with a gurobi solver. Computational results demonstrate and compare the effectiveness of the two formulations.


2015 ◽  
Vol 21 (4) ◽  
pp. 949-964 ◽  
Author(s):  
Alejandro Hidalgo-Paniagua ◽  
Miguel A. Vega-Rodríguez ◽  
Joaquín Ferruz ◽  
Nieves Pavón

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Ümit Yerlikaya ◽  
R.Tuna Balkan

Abstract Instead of using the tedious process of manual positioning, an off-line path planning algorithm has been developed for military turrets to improve their accuracy and efficiency. In the scope of this research, an algorithm is proposed to search a path in three different types of configuration spaces which are rectangular-, circular-, and torus-shaped by providing three converging options named as fast, medium, and optimum depending on the application. With the help of the proposed algorithm, 4-dimensional (D) path planning problem was realized as 2-D + 2-D by using six sequences and their options. The results obtained were simulated and no collision was observed between any bodies in these three options.


Author(s):  
Duane W. Storti ◽  
Debasish Dutta

Abstract We consider the path planning problem for a spherical object moving through a three-dimensional environment composed of spherical obstacles. Given a starting point and a terminal or target point, we wish to determine a collision free path from start to target for the moving sphere. We define an interference index to count the number of configuration space obstacles whose surfaces interfere simultaneously. In this paper, we present algorithms for navigating the sphere when the interference index is ≤ 2. While a global calculation is necessary to characterize the environment as a whole, only local knowledge is needed for path construction.


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