Abstract
Aiming at the former formalized methods of robot planning should give the environment state, can not obtain the new knowledge of the environment. In order to improve the reason ability for obtaining new knowledge of the environment state, the actions in the process of planning such as external action and sensing action are formalized. A formalized reasoning method—CPNI (Colored Petri Net for Planning in incomplete environment) based on two kinds of actions is proposed, and the reasoning rule as Fluent Calculus in incomplete environment is applied. Robot planning experiment is modeled and simulated by using the tool CPNTools and the result shows the state knowledge of the door and the action sequence to reach the goal can be generated automatically in the CPNI net system.
Highlights
Robot planning [1] is the behavior planning process to reach the goal, it mainly includes two problems: generate the action sequence to reach the goal, and obtain the dynamic knowledge in the process of reasoning.Petri net [2,3] is a formalized description tool and suitable model for modeling the system characterized by synchronism, dynamics, concurrency
Vittorio [5] introduced a method for robot planning based on Petri net, formally describing actions and the relations between the actions, but it lacks the formal description for the state including the environment state and robot state, can not generate automatically the action sequence to the goal, and can not represent the incomplete knowledge
The sensor is introduced into the robot, converting the process of sensing the state to the sensing action of the according CPNI net system, through the sensing action, the robot can get the new knowledge of the world state, realizing the representation of the dynamic and unknown environment and reasoning in an incomplete environment
Summary
Robot planning [1] is the behavior planning process to reach the goal, it mainly includes two problems: generate the action sequence to reach the goal, and obtain the dynamic knowledge in the process of reasoning. Vittorio [5] introduced a method for robot planning based on Petri net, formally describing actions and the relations between the actions, but it lacks the formal description for the state including the environment state and robot state, can not generate automatically the action sequence to the goal, and can not represent the incomplete knowledge. The above work can not realize the robot planning, namely, automatically generate the action sequence to the goal and obtain the knowledge in the process of the reasoning, realizing robot planning in incomplete environment. The sensor is introduced into the robot, converting the process of sensing the state to the sensing action of the according CPNI net system, through the sensing action, the robot can get the new knowledge of the world state, realizing the representation of the dynamic and unknown environment and reasoning in an incomplete environment. The Fluent Calculus [6,7], sensing action and the external action are introduced to the generating algorism of the CPNI net system, the generated CPNI net system can realize robot planning and the dynamic knowledge of the robot reasoning
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