Mobile robots are expected to support relief activities, after a great scale disaster. These robots need ability to move on/in rubble in order to gather information related to victims and conditions. However, there is no mobile robot which has enough movement ability. Mobile robots need big bodies in order to traverse on unstructured terrain composed of big rubbles, but they need small bodies in order to enter in narrow space. In this paper, we proposed novel concept of a transformational mobile robot in order to solve this inconsistency, and manufactured the proposed mechanism and evaluated its fundamental movement ability.

This paper presents a new hierarchical scheduling method for a large-scale production system based on a hierarchical Petri net model, which consists of FOHPN and TPN. The automobile production system equipped with 2 stand-by lines is focused as one of a typical large-scale system and these stand-by lines are controlled by binary signal. In a high level, the FOHPN model is used to represent continuous flow in production of an entire system, and MLD description is used to control the net dynamics of FOHPN. Also in a low level, TPN is used to represent production environment of each sub-line in a decentralized manner, and MCT algorithm is applied to find a feasible semi-optimal process sequences for each sub-line.

Presents a scheduling method for a manufacturing system based on a timed Petri net model and a reactive fast search algorithm. The following two typical problems are addressed in the paper. (1) Minimize the maximum completion time. (2) Minimize the total deadline over-time. As for problem (1), a search algorithm which combines RTA* and a rule-based supervisor is proposed. Since both RTA* and the rule-based supervisor can be executed in a reactive manner, machines and AGVs allocations can be scheduled reactively, and simultaneously. As for problem (2), the original Petri net model is converted to its reverse model and the algorithm developed in problem (1) is applied with regard to the due time as a starting time in the reverse model.

This paper studies the learning control problem of disassembly task sequence. The proposed learning control system has two sub systems. One of them is a supervisory control system which can realize the implicit specifications such as equipment-related or task-independent specifications. The other one is a learning automata system which can realize the explicit specifications such as task-dependent specifications. This approach allows the flexible design to accommodate frequently changing manufacturing requirements. Some simulation results to verify the effectiveness of the proposed system are shown.

An automatic generation of assembly or disassembly sequence is a significant problem for an automatic assembly using robotic manipulators. This problem can be separated into following three stages. 1. Extraction of all feasible assembly/disassembly tasks. 2. Generation of all assembly/disassembly sequence. 3. Decision of optimal sequence. As for the stages 2 and 3, one of the efficient strategy based in the AND/OR graph has been proposed. However, as for 1, previous researches are not efficient. In this paper we propose a new technique for the examination of the feasibility of each assembly/disassembly task by using topological operations. The presented method is expected to execute with smaller computational amount compared with the previous methods, because a separating path of a mechanical part without collision with other parts is obtained without search of all space. A mapping, which maps shape of a subassembly to a feasible path of the other subassembly around the first subassembly, keeping contact, is introduced. An area of feasible translational motion of the second subassembly without interaction with the first is calculated. Criteria of feasibility of disassembly task are presented. Finally, we show a simple example to verify the proposed algorithm.>

An assembly planning method using Petri nets is presented. First, the assembly network is modeled using the conventional AND/OR net. Second, the state shift equation of the Petri net, which is its mathematical model, is analyzed. This analysis shows that the basis solution the of a state shift matrix is identical to the set of a solution which corresponds to an actual assembly sequence. This means that in considering an optimization problem which minimizes a summation of a weight value of all tasks included in the assembly sequence, a linear programming technique can be used. Some numerical examples are given to certify the validity of the analysis.