Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: For autonomous assembly operations by a robot, it is required to build a planning function that can generate a series of operations to reach a goal state.  describes an automatic planning algorithm that synthesizes the assembly operation strategies. By minimizing a criterion function based on the difficulty of state transitions the method can find an optimal path in a contact state network. The degree of constraint is proposed by regarding the assembly task as a process of changing the constraint state of the object. State transition difficulty is discussed by considering the variation of the degree of constraint and the shape information from the geometric models of objects. Then, a criterion function for state transitions is defined based on the state transition difficulty. Lastly, an algorithm which plans an optimal state transition path from an initial state to a goal state is proposed. Some examples are given to show the validity of this algorithm. >
['Tsuneo Yoshikawa', 'Yasuyoshi Yokokohji', 'Yong Yu']
I am writing a research paper on a idea Assembly planning operation strategies based on the degree of constraint
[{"from": "human", "value": "I am writing a research paper on a idea Assembly planning operation strategies based on the degree of constraint"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: For autonomous assembly operations by a robot, it is required to build a planning function that can generate a series of operations to reach a goal state.  describes an automatic planning algorithm that synthesizes the assembly operation strategies. By minimizing a criterion function based on the difficulty of state transitions the method can find an optimal path in a contact state network. The degree of constraint is proposed by regarding the assembly task as a process of changing the constraint state of the object. State transition difficulty is discussed by considering the variation of the degree of constraint and the shape information from the geometric models of objects. Then, a criterion function for state transitions is defined based on the state transition difficulty. Lastly, an algorithm which plans an optimal state transition path from an initial state to a goal state is proposed. Some examples are given to show the validity of this algorithm. >"}]