R. C. Arkin and D. MacKenzie, "Temporal coordination of perceptual algorithms for mobile robot navigation," IEEE Transactions on Robotics and Automation, vol. 10, no. 3, pp. 276--286, 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....approaches such as schema based methods [6] or action selection [71] su er from the same problems since they do not provide any tools for a principled re design if the task changes. This has led to combining basic behaviors with a sequencer to derive control as a sequences of parallel behaviors [5, 107]. Here, radical changes in the task requirements can be addressed by modifying the set of behavioral modules and their sequencing rather than by adding additional layers as in subsumption. This reduces the number and type of control interactions and thus the risk of brittleness due to ....

Arkin, R.C., and MacKenzie, D. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Trans. Robotics Automat. 10, 3 (June 1994), 276-286.

....on the other hand there are behaviour based controllers that are far less brittle, better able to cope with the noise and variation inherent in the real world, but which, as yet, lack the facility to specify higher level goals. There have been attempts to combine both approaches ( Simmons 94, Arkin MacKenzie 94] we believe, however, that goal directed and seemingly intelligent behaviour need not necessarily be defined using symbolic representations, and have therefore concentrated on behaviourbased controllers, using as little symbolic representation as possible, no symbolic world model, and a tight ....

R. Arkin and D. MacKenzie, Temporal coordination of perceptual algorithms for mobile robot navigation, IEEE Trans. Robotics and Automation, Vol.10, No.3, 1994.

....systems. These systems can either be simple, reactive systems or more complex hierarchical configurations that take advantage of learning and memory. At the basis of Clay are perceptual, motor schema and action nodes that are combined within the Hammerhead control system as behavioral sequences [5]. Perceptual nodes take information from the vision system and bump sensor as to the location of objects of interest or obstacles. These perceptual nodes are fed into motor schema nodes that produce vectors representing the desired trajectory of the robot. Action nodes are then formed by the ....

R. Arkin and D. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(33):276--286, June 1994.

....set. This method of selecting the active behaviour set can not be used if the task requires an ordered sequence of behaviours. An alternate approach to modelling tasks that does not suffer from ordered behaviour sequencing has been recently proposed by Arkin and MacKenzie for perceptual processes [6]. Their approach controls sequences of perceptual algorithms using a finite state model with transitions between states triggered by either elapsed time, algorithm completion, algorithm failure, or termination of a motor activity. A priority based mechanism is used to handle the simultaneous ....

....topology. Behavioural space refers to the partition of the environment made by the animal s (or robot s) sensory system. Tasks are defined by their initial and final states using state variables that are relevant to the task. Finite state automata (FSA) have been used to model perceptual tasks [6] and motivational behaviour in animals [64, 46] Arkin and McKenzie have used FSA to model the space time relationship in a perceptual processing task on a mobile robot. This approach allows for perceptual tasks to be sequenced in a reactive control system. In short, finite state automata used to ....

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Ronald C. Arkin and Douglas MacKenzie. Temporal coordination of perceptual algorithms for a mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, June 1994.

....based control strategy, in which some basic behaviors are defined and appropriate behavior is selected which is good for carrying out the given task. Thus the sequence of decision making for appropriate action is similar to that of human being. In addition to the behavior based control, Arkin[2][3] introduced the reactive control scheme which is based on some basic behaviors and each robot select its own behaviors according to the current environment and the given task. The robot soccer game that we introduced in this paper is played by three robots per each team, and each of three robots ....

Ronald C. Arkin and Douglas Mackenzie, "Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation," IEEE Trans. on Robotics and Automation, Vol.10, No.3, pp.276-286, June 1994

....task. 3 Behaviors for foraging A motor schema based reactive control system is used for robot programming [2] In this approach, the agent is provided several pre programmed behavioral assemblages that correspond to steps in achieving the task (e.g. wander, acquire, deliver, and so on [1]) The behavioral assemblages are in turn composed of more primitive behaviors called motor schemas. Binary perceptual features (also referred to as perceptual triggers) are used to sequence the robot through steps in achieving the task. Three strategies for foraging are implemented and evaluated ....

....as Finite State Automata (FSAs) that sequence from one state to another. Each state of the FSA determines which behavior is to be activated, with transitions between behavioral states triggered when particular perceptual features are activated. This approach is called perceptual sequencing [1]. A fixed set of perceptual features are utilized across all implementations to ensure a fair comparison between the various foraging systems. The perceptual features for foraging are cataloged in Table 1. In addition to the features advising the robot whether an attractor is visible, there are ....

R. Arkin and D. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, June 1994.

....obstacle avoided obstacle on path Avoid Obstacle Stop obstacle on path door not traversed Figure 6: An example FSA encoding a door traversal behavior. 7. 2 Temporal Sequencing [Arkin MacKenzie 94] The temporal sequencing approach also known as perceptual sequencing and sequenced coordination [6] is very similar to the discrete event system approach. A finite state automaton is used for formulating a mechanism for sequencing between a series of behaviors based on perceptual triggers. At each state a distinct behavior is activated and perceptual triggers cause transitions from one state to ....

Ronald C. Arkin and Douglas MacKenzie. Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, June 1994.

....allow us to construct models with more complex geometries. 2.3 Visual schemas A visual schema is the search engine which locates interesting image regions and matches them against a geometry model. Schema has been used in many contexts in computer vision; our usage comes most nearly from Arkin[2], who used the term perceptual schema to describe a virtual sensor which, when activated, triggered state changes in robot motor control laws. In Argus, a visual schema is similarly a virtual sensor, tuned to a specific set of features and geometric constraints. Visual schemas create and monitor ....

Ronald C. Arkin and Douglas MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Trans. on Robotics and Automation, 10(3):276--286, 1994.

....sequence are separate behavioral states. Perceptual events that cause transitions from one behavioral state to another are called perceptual triggers. The resulting task solving strategy can be represented as a Finite State Automaton (FSA) The technique is referred to as temporal sequencing [ Arkin and MacKenzie, 1994 ] Figure 1: Motor schema example. The diagram on the left shows a vector field corresponding to a move to goal schema, pulling the robot to a location on the right. The center diagram shows an avoid obstacles field, repelling the robot from two sensed obstacles. On the right, the two schemas ....

R.C. Arkin and D.C. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, 1994.

....to solve and those that are simple in the sense that one predesigned strategy is sufficient to handle the entire scenario. A more complex approach for module activation is to precompile switching circuitry into the architecture that activates relevant modules under specific conditions (e.g. [4,7,50]) For example, a trash collecting robot might wander looking for an empty can on the floor. During this condition, only the modules avoid obstacle and wander would be active. Once the robot detects a can, it can deactivate the wandering behavior and activate a module responsible for approaching ....

....environment with very few obstacles, this parameter should be reduced so as to permit the robot to take a relatively direct path towards the goal. As mentioned previously, one approach to coordinate motor schema based behaviors is to precompile their priorities (or gains) at design time (e.g. [4]) In this approach, the designers know the types of situations the robot may encounter and the appropriate coordination scheme to use under those situations. Thus, the robot must simple detect under what situation is currently navigating and use the precompiled coordination scheme to successfully ....

R.C. Arkin and D.C. MacKenzie, Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation, IEEE Transactions on Robotics and Automation 10(3) (1994) 276--286.

....goals in a timely fashion, avoid deadlock, and do not incur heavy communication costs provides a challenging task. Multi agent planning and negotiation techniques are common in the AI literature [7, 10, 11, 17, 20, 24] but have not been integrated into computer vision work. Some research [2, 14] has focused on developing centralized and distributed methods for multi agent planning specifically in the context of the Unmanned Ground Vehicle project. Again, these projects focus on planning for navigation of the vehicles. Very little work has been investigated on multi agent techniques for ....

R. C. Arkin and D. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276-- 286, 1994.

....is expected given the robot s belief about the object s position, and its own relative position and motion. This increases the robustness of identification, and prevents accumulation of the uncertainty inherent in the navigation and odometry. To solve complex autonomous tasks, Arkin and MacKenzie [1] presented a methodology for breaking tasks into a sequence of temporally integrated perceptual algorithms and transitions between these algorithms. The system presented here could be applied in such a methodology. The robot would initially move close to the object using other methods available in ....

....system requires a world model, in which workstation location and pose are specified. Arkin and MacKenzie [2] break the type of navigation task presented by Rembold into ballistic and controlled movement. Such a breakdown facilitates temporal sequencing of several algorithms for different tasks [1]. In ballistic motion the robot moves rapidly in the general direction of the desired object guided by a so called phototropic perception algorithm, which attracts the robot to bright light. A transition occurs when the robot recognises the required object. It then moves in a controlled fashion, ....

R. C. Arkin and D. MacKenzie, Temporal coordination of perceptual algorithms for mobile robot navigation, IEEE Trans on Robotics and Automation, 10(3) (1994).

....methodology, permitting the recursive formulation of societies of robots. A society is viewed as an agent consisting of a collection of either homogeneous or heterogeneous robots. Each individual robotic agent consists of assemblages of behaviors, coordinated in various ways. Temporal sequencing [10] affords transitions between various behavioral states which are naturally represented as a finite state acceptor. Coordination of parallel behaviors can be accomplished via fusion, actionselection, priority, or other means as necessary. These individual behavioral assemblages consist of groups of ....

....on our control methods for robotic systems. Exemplified by our multiagent research, we have demonstrated a system which uses homogeneous units to carry out tasks of foraging, grazing, and consuming objects in a cluttered world [12,13] We have extended our 16 research in schema based navigation [4,10] to include patterned sequences of behaviors [1] and their use in multiagent navigation. This approach to reactive navigation has been previously demonstrated in a variety of application domains. Emergent behavior is evidenced as the phenomena of recruitment, the shared effort of many robots to ....

Arkin, R.C. and MacKenzie, D., "Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation", IEEE Transactions on Robotics and Automation, Vol. 10, No. 3, June 1994.

....decomposed in Level b to show the two individuals. Level c shows the various operating states present in each of the two fish to support the mating ritual. The linear chain of behaviors shown in Figure 1 can be represented as a Finite State Automaton (FSA) using the methods of Temporal Sequencing [4]. Temporal sequencing formalizes methods for partitioning a mission into discrete operating states and describing the transitions between states. The FSA is partitioned into the relevant male and female portions and distributed within the respective robots (fish) However, the abstraction remains ....

....the definition of suppress in Equation 4, behav3 correctly dominates when it is valid, otherwise behav2 dominates behav1 when it has valid data and behav1 is only allowed to generate an output when both of the other behaviors are not generating useful data. Temporal Sequencing Temporal sequencing [4] is a state based coordination mechanism which uses a Finite State Automaton (FSA) 20] 1] to select one of several possible operating states based on the current state, the transition function, and perceptual triggers. Each state in the FSA denotes a particular member agent which is dominant ....

R.C. Arkin and D.C. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, June 1994.

....methods for robotic systems. Exemplifying our multiagent research, we have demonstrated a system which uses homogeneous units to carry out tasks of foraging and retrieval of objects, grazing, and consuming objects in a cluttered world [11] We have extended our research in schema based navigation [4,3] to include patterned sequences of behaviors [1] and their use in multiagent navigation. This approach to reactive navigation has been previously demonstrated in a variety of application domains. Emergent behavior is evidenced as the phenomena of recruitment, the shared effort of many robots to ....

Arkin, R.C. and MacKenzie, D., "Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation ", to appear in IEEE Transactions on Robotics and Automation, Vol. 10, No. 3, June 1994. .

....their baseline parameters are described. At the highest level, the tasks themselves are assemblages which are represented as finite state acceptors (FSAs) consisting of several states. FSAs provide an easy means for both expressing and reasoning about behavioral sets by providing formal semantics [11]. Each state corresponds to a separate assemblage in which a constituent set of motor schemas is instantiated if that particular state is active. P erceptual T riggers cause transitions between states. Each active motor schema has a perceptual schema associated with it to provide the information ....

Arkin, R.C. and MacKenzie, D., 1994. "Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation", to appear in IEEE Transactions on Robotics and Automation.

....permits rapid computation of the desired joint velocities without the use of inverse kinematics. In this paper, a drum sampling task is presented where the vehicle demonstrates how a sample of material could be moved from one drum to a second. This task integrates our work in temporal sequencing[3] with our research in visual tracking[19] and visual servoing[17] Images taken from a robot waist camera are processed using a constrained, line based Hough transform[19, 14] to recognize and localize the drums in natural settings using a stored model. The perceptual process provides the ....

....the drum. The process is then repeated for the second drum to show how additional samples could be collected. Finally, the vehicle halts after finishing with the second drum. The behavioral configuration which implements this drum sampling task uses two levels of temporal sequenced coordination[3] to control execution of the various stages of the mission. Figure 5 shows the toplevel coordination operator which causes the manipulator to demonstrate how a sample of material could be moved from one drum to a second. start sample drum(take) sample drum(put) end Figure 5: FSA to move samples ....

Arkin, R.C. and MacKenzie, D., "Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation", IEEE Transactions on Robotics and Automation, Vol 10, No. 3, June 1994, Pg 276-286.

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R. C. Arkin and D. MacKenzie, "Temporal coordination of perceptual algorithms for mobile robot navigation," IEEE Transactions on Robotics and Automation, vol. 10, no. 3, pp. 276--286, 1994.

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R.C. Arkin and D. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, June 1994.

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R. C. Arkin and D. MacKenzie, "Temporal coordination of perceptual algorithms for mobile robot navigation," IEEE Transactions on Robotics and Automation, vol. 10, no. 3, pp. 276--286, 1994.

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Ronald Arkin and Douglas MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(33):276--286, June 1994.

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R. C. Arkin and D. MacKenzie, "Temporal coordination of perceptual algorithms for mobile robot navigation," IEEE Trans. Robot. Automat., vol. 10, pp. 276--286, June 1994.

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R. C. Arkin and D. McKenzie, #Temporal coordination of perceptual algorithms for mobile robot navigation," IEEE Trans. on Robotics and Automation 10#3#, pp. 276#286, 1994.

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R. Arkin and D. MacKenzie. Temporal coordination of perceptual algorithms for mobile robot navigation. IEEE Transactions on Robotics and Automation, 10(3):276--286, June 1994.

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Ronald C. Arkin and Douglas Mackenzie, "Temporal Coordination of Perceptual Algorithms for Mobile Robot Navigation," IEEE Trans. on Robotics and Automation, Vol.10, No.3, pp.276-286, June 1994

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