Norisuke Fujii

Rearrangement task realization by multiple mobile robots with efficient calculation of task constraints

We address a rearrangement task by multiple robot in this paper. A rearrangement task has constraints regarding the order of the start, grasping and finish time. Calculating these constraints has a high computational cost. We propose a rearrangement method that calculates constraints efficiently. In our approach, not all constraints are calculated, but some of them will be calculated step by step. The proposed method is tested in a simulated environment with up to 4 mobile robots. The methods are compared, and the results indicate that the proposed method is superior.

Multiple Robot Rearrangement Planning Using a Territorial Approach and an Extended Project Scheduling Problem Solver

In this paper, we address a multiple robot rearrangement problem. For different applications, problem-solving methods should be able to cope with various working environments. We focus on small working environments in particular with a concentrated arrangement of objects and narrow corridors. In this type of environment, the rearrangement problem can be very complicated because of high computational cost for priority settings to prevent robots from colliding and constraints related to the order of transportation. We propose a practical algorithm that divides a complicated rearrangement problem into simple subproblems. In our method, the rearrangement problem can be reduced to a project scheduling problem using a territorial approach. The application of a territorial approach can relax the complexity of priority settings, but yields new kinds of constraints at the same time. We propose an extended project scheduling problem solver to address these constraints. The solver is constructed on the basis of meta-heuristic strategy and generates the order of transportation that observes constraints. The proposed method is tested in a simulated environment with up to four mobile robots and 12 movable objects. Simulation results show the effectiveness of our method with respect to the applicability and a reasonable calculation time.

Territorial and Effective Task Decomposition for Rearrangement Planning of Multiple Objects by Multiple Mobile Robots

In this paper, we address a rearrangement task planning problem. The method proposed here is suitable for various environments with narrow corridors, and an unbalanced arrangement of robots and objects. As the solution space is too large for the search method to be applied directly, we will limit the search space. The proposed method develops an initial plan by using a simple rule and improves the task decomposition of the initial plan. That is, it effectively determines which object should be transported where. We employ the concept of the critical path method to select the task that should be modified and the concept of a territorial approach to set up new task decomposition. New task decomposition is set up so that a robot can operate without considering the movement of other robots. These concepts render our method fast. The proposed method is tested in a simulated environment with up to four robots and 12 movable objects. The simulation results show that in a feasible calculation time, our method can reduce the task time by 10% as compared to the previous method. In particular, the proposed method is much more applicable to the working environments than was the previous method.

Realization of a Multiple Object Rearrangement Task with Two Multi-Task Functional Robots

A rearrangement task of multiple objects is discussed here. In this paper, robots that carry more than one object simultaneously are referred to as multi-task functional, whereas a standard single-task robot carries one object at a time. With multi-task functional robots, the total length of transfer paths is shortened and the processing time is reduced. We propose a planning algorithm that consists of simulated annealing and a scheduling method using prioritization rules for a group of multi-task functional robots. We also propose a planning methodology on synchronization timing between the robots. Experiments involving two robots were conducted in real and simulated environments to show the effectiveness of the proposed algorithms.

Multiple robot rearrangement problem using an extended project-scheduling problem solver

In this paper, we address a multiple robot rearrangement problem. We focus on a small working environment composed of narrow corridors. In such an environment, adequate priority settings are required to prevent robots from having collisions. As a result, enormous calculation time is required. We propose a practical method utilizing partitions that divide the entire complicated problem into multiple simple sub-problems. Among these sub-problems, new constraints related to task execution order occur. Therefore, we extend the existing project-scheduling problem solver to cope with these new constraints. The proposed method is tested in a simulated environment with up to 4 mobile robots and 12 movable objects. The simulation results show that our method can be used to obtain a solution in a feasible calculation time.

Rearrangement of multiple objects by a robot group having a multi-task function

A robot having a multi-task function can carry more than two objects simultaneously; however, a robot without that function can carry only one at any given time. A multi-task function robot has the potential to shorten the transfer path, which reduces the process time; however, a single-function robot does not have that capability. In this paper, a planning algorithm that consists of Simulated Annealing and Scheduling with prioritization rules for a robot group having a multi-task function is proposed. Experiments are conducted in a real environment to validate the proposed algorithms.

Rearrangement Task by Multiple Robots Using a Territorial Approach

In this paper, we address a rearrangement task involving multiple robots. We focus on small working environments composed of narrow corridors. In such an environment, interference between robots resulting from a competition for physical space can affect the overall performance in a rearrangement task. Because of the enormous amount of calculation time required to develop a motion plan for each robot considering the effect of interference, it is difficult to apply the former approach directly. In this paper, we propose a practical method using a territorial approach where the working area of each robot is defined so that there is no overlap. Because robots can develop a motion plan with less consideration of interference between other robots, the entire calculation time can be reduced. In this method, we obtain the order of sub-task executions as a solution to a project scheduling problem. However, some constraints that have not been dealt with in research involving scheduling may arise. We analyzed these new constraints and proposed a metaheuristic strategy to determine the order of sub-tasks. The proposed method is tested in a simulated environment with up to four mobile robots, 12 movable objects, and a complicated arrangement of objects.

Position management system for an indoor group of forklifts with a sensor network

A position management system for forklifts involved in a warehouse storage task is proposed. With a simple, low-cost laser beam sensor and reflective stickers, the position of the forklift can be established. Furthermore, by combining probability estimation algorithms, the possible location of forklifts can be managed and the accuracy of positioning can be improved through the exchange of information on a sensor network. With this system, forklift operations are easier, and the cost of a warehouse navigation system decreases.

LOW-COST AND ROBUST POSITIONING SYSTEM FOR INDOOR GROUP OF FORKLIFTS UTILIZING PROBABILITY ESTIMATION AND SENSOR NETWORK

A position management system for forklifts involved in a warehouse storage task is proposed. With a simple, low-cost laser beam sensor and reflective stickers, the position of the forklift can be established. Furthermore, by combining probability estimation algorithms, the possible location of forklifts can be managed, and the accuracy of positioning can be improved through the exchange of information on a sensor network. Finally, the layout, which has a better system performance, is also discussed and proposed. With this system, forklift operations are easier, and the cost of a warehouse navigation system decreases.