D.C. MacKenzie, J.M. Cameron, and R.C. Arkin. Specification and execution of multiagent missions. In IEEE International Workshop on Intelligent Robots and Systems (IROS '95), 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....2. Problems where cooperation increases performance either by decreasing the time to complete the task, or by increasing the reliability. Sample tasks include cleaning up trash or mapping a large area. This type of cooperation depends most often on communication for information sharing (MacKenzie, Arkin, Cameron 1997; Mataric 1997; Parker 1996; Schneider Fontan Mataric 1996) but has also been demonstrated without explicit communication (Arkin 1992; Beckers, Holland, Deneubourg 1994) However, even simple communication has been shown to increase substantially the performance of robots when foraging, ....

MacKenzie, D.; Arkin, R. C.; and Cameron, R. 1997. Specification and execution of multiagent missions. Autonomous Robots 4(1):29--57.

.... or more robots by modeling their overall behavior as a collections of simpler, interacting behaviors (similar to Minsky s model of the brain) MacKenzie, Cameron, and Arkin describe a framework for controlling a society of robots that must cooperate to jointly perform military scouting missions [27]. Mataric, Nilsson and Simarian [29] describe an approach for coordinating multiple robots to work together to push boxes. 5.2 Web Based Agents, and Electronic Personal Assistants An increasingly common type of agents are Web based agents that take advantage of the network of information that ....

# D.C. MacKenzie, J.M. Cameron, and R.C. Arkin, "Specification and Execution of Multiagent Missions," Proc. IEEE/RSJ Int'l Conf. Intelligent Robots and Systems, vol. 3, pp. 51-58, Aug. 1995.

....it consists of Exploration and Regression tree induction to produce Action models. During the exploration phase the robot collects data using a simple wander program to navigate through the environment. Currently, we are experimenting with ERA in simulation based on Georgia Tech s MissionLab (MacKenzie et al. 1995). In its original form, MissionLab allows a robot to move about the environment and sense obstacles and other robots. We have extended this environment by creating terrain elements and adding noise to robot actions. In this paper we focus on the MoveForward action as it is used to support the high ....

MacKenzie, D., Cameron, J., & Arkin, R. C. (1995). Specification and execution of multiagent missions. Proceeding sof the International Conference on Intelligent Robotics and Systems (IROS '95) (pp. 51-- 58).

....to its superior an agent is viewed as an action. This is illustrated in figure 2. 5 A taxonomy for action selection mechanisms Classification of existing action selection mechanisms (ASMs) into a number of logical groups can be useful. In the review of the literature we find two taxonomies ([32] and [56] that suggest schemes for classification of ASMs. Agent Agent Agent Agent Agent Agent Agent agents actions Role wrt. subordinate action selection mechanism action Role wrt. superior agent Figure 2: Internal view of agencies. The two roles of an agent in the agent hierarchy. From its ....

....agent Figure 2: Internal view of agencies. The two roles of an agent in the agent hierarchy. From its own point of view an agent is an action selection mechanism whereas from a superior s point of view it is an action. Figure 3 shows a classification of coordination mechanisms suggested in [32]. The classification divides coordination mechanisms into state based and continuous. These terms are, however, not explained in [32] thus the following is our understanding of the terms. In a given state only a relevant subset of the robot s behavior repertoire needs to be activated. State based ....

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Douglas C. Mackenzie, Ronald C. Arkin, and Jonathan M. Cameron. Specification and Execution of Multiagent Missions. Autonomous Robots, 4(1), Januray 1997.

....that each robot has its own individual waypoints, and its path is shown on the layout in the same color as the robot (each robot has its own separate color in the layout) 4. 3 Underlying Robot Architecture These multiagent telerobotic interfaces have been incorporated into the MissionLab system [33]. MissionLab is a system for specifying, simulating, and executing multiagent mobile robot missions. MissionLab takes high level specifications and executes them with teams of real or simulated robot vehicles. It provides tools for quickly creating behavior based robot programs, which can then be ....

D. MacKenzie, J. Cameron, and R. Arkin. Specification and execution of multiagent missions. In Proc. 1995 Int. Conf. on Intelligent Robotics and Systems IROS '95, pages 51--58, 1995.

....small spaces. Telop was tested on a pair of Denning MRV 2 mobile robots, each about three feet tall with a diameter of 32 inches. Each robot is equipped with a ring of 24 ultrasonic sensors and shaft encoders. A Sun Sparcstation 5 served as the base station, running Telop through MissionLab 1 [11]. The base station communicates with the robots using FreeWave radio links. The base station and human operator were on the third floor of the Manufacturing Research Center at Georgia Tech, and the robots were running on the first floor. The feedback to the operator consisted of the graphical ....

MacKenzie, D., Cameron, J., Arkin, R., "Specification and Execution of Multiagent Missions", Proc. 1995 Int. Conf. on Intelligent Robotics and Systems IROS '95, Pittsburg, PA, Vol. 3, pp. 51-58, 1995.

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MacKenzie, D., Cameron, J., Arkin, R., "Specification and Execution of Multiagent Missions", Proc. 1995 International Conference on Intelligent Robotics and Systems (IROS '95), Pittsburg, PA, 1995, pp. 51-58.

....together within the context of action oriented perception. Dempster Shafer statistical methods provide the basis for evidential reasoning. ffl The original rule based Plan Sequencer has been replaced with a temporal sequencer [16] that traverses a finite state acceptor (FSA) expression of a plan [37]. Each state of the FSA represents a specific combination of behaviors that accomplish one step of the task. Transitions are made from one state to another when significant perceptual events trigger them. Another strength of AuRA is the flexibility it provides for introducing adaptation and ....

.... have been applied in a variety of domains including: ffl Manufacturing environments [18] ffl Three Dimensional navigation as found in aerial or undersea domains [14] ffl Indoor and outdoor navigation [6] ffl Robot competitions [15, 19] ffl Vacuuming [36] ffl Military scenarios [37, 20]. ffl Mobile Manipulation [23] ffl Multi robot teams [13, 21] Several of these robotic systems are described in in more detail in Section 4. Finally, one of the major strengths of AuRA results from the power of wedding two distinct AI paradigms: deliberation and reactivity. The advantages of ....

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MacKenzie, D., Cameron, J., Arkin, R., "Specification and Execution of Multiagent Missions", to appear Proc. 1995 Int. Conf. on Intelligent Robotics and Systems IROS '95, Pittsburg, PA.

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MacKenzie, D., Cameron, J., Arkin, R., "Specification and Execution of Multiagent Missions", Proc. 1995 Int. Conf. on Intelligent Robotics and Systems IROS '95, Pittsburgh, PA, Vol. 3, pp. 51-58.

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D.C. MacKenzie, J.M. Cameron, and R.C. Arkin. Specification and execution of multiagent missions. In IEEE International Workshop on Intelligent Robots and Systems (IROS '95), 1995.

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D. C. Mackenzie, R. C. Arkin, and J. M. Cameron, "Specification and Execution of Multiagent Missions," Autonomous Robots 4, Januray 1997.

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