P. Svestka and M. Overmars. Coordinated path planning for multiple robots. Robotics and Autonomous Systems, 23(3):125--152, Apr. 1998.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....treated as though they were a deadlock, where no robot is able to make progress. Previous work on deadlocks in robot applications fall into several categories. Lin and Hsu [26] approach deadlocking from the classi cal operating system perspective. Hartonas Garmhausen [27] Qutub [28] and Svestka [29] represent the problem as a graph with centralized planning, which is incompatible with the desire for a distributed, reactive solution. Fukuda [30] and Kube [31] utilize changes in behaviors to break deadlocks. Hara [32] removes the deadlock from the system by changing the physical configuration ....

P. Svestka and M. Overmars, "Coordinated path planning for multiple robots," in Robotics and Autonomous System, 1998, pp. 125-152.

....spaces. This drawback has lead to the development of several randomized methods that can search high dimensional configuration spaces quickly at the cost of losing optimality. For example, one randomized planning technique, Probabilistic Road Maps, was applied to multi robot systems in [24]. Another example is [6] where randomization is used to coordinate the time stamps on independently constructed trajectories. To relax the problem of searching through highdimensional configuration spaces, several decentralized motion planning strategies have been developed. Their distributed ....

P. Svestka, & M. H. Overmars, "Coordinated Path Planning for Multiple Robots," Technical Report UU-CS-1996-43, Utrecht University, The Netherlands, 13, 1996.

....formation. They demonstrate their results on a team of three physical robots. VII. MOTION COORDINATION Another popular topic of study in multi robot teams is that of motion coordination. Research themes in this domain that have been particularly well studied include multi robot path planning [63], 41] 30] 69] traffic control [55] formation generation [2] and formation keeping [13] 66] Most of these issues are now fairly well understood, although demonstration of these techniques in physical multi robot teams (rather than in simulation) has been limited. More recent issues ....

P. Svestka and M. H. Overmars. Coordinated path planning for multiple robots. Robotics and Autonomous Systems, 23(3):125--152, 1998.

....in complexity. Moreover, the approach considers that all news about the robots and their environment can be consigned to a single location for elaborating and that this information does not modify during the time that an optimal plan is built. Jensen and Veloso [11] Svestka and Overmars cite[16], and Brumitt and Stentz cite[9] are examples of the centralized approach to manage a multi robot system structured hierarchically. The above considerations are ivory towers for problems in which the environment is unknown and or changing, communication is limited, and robots behave in ....

P. Svestka and M. H. Overmars, `Coordinated path planning for multiple robots', Robotics and Autonomous Systems, 23(4), 125--133, (1998).

....convey relevant information to the leader, and execute the plans generated by the leader. Some examples of such centralized approaches can be found in work done by Caloud et al. 14] Chaimowicz et al. 16] Jensen and Veloso [35] Brummit and Stentz [11] Simmons et al. 69] Svestka and Overmars [74], and Burgard et al. 12] The principal advantage of such centralized approaches is that optimal plans can be produced. The leader can take into account all the relevant information conveyed by the members of the team and generate an optimal plan for the team. However, centralized approaches ....

Svestka, P., Overmars, M. H., "Coordinated Path Planning for Multiple Robots", Robotics and Autonomous Systems, Vol. 23, No. 4, pp. 125-133, 1998.

....15] have made e orts to quantify the approach and determine bounds on the number of points that should be examined to nd a solution with a given probability. This approach has been extended to handle robots with nonholonomic constraints [30] and when multiple robots are moving in the environment [31]. Barraquand and Latombe [6] combine randomization with a potential eld method to solve the motion planning problem. Their approach uses potential functions to plan the general motions of the robot and the randomization enters the algorithm if the robot enters a local minimum that is not the ....

P.  Svestka and M. H. Overmars. Coordinated path planning for multiple robots. Technical Report UU-CS-1996-43, Utrecht University, the Netherlands, 1996. 13

....and then searching for a path in the roadmap connecting these nodes. The algorithms are easy to implement, run quickly, and are applicable to a wide variety of robots. In [25] this method is applied to an articulated robotic arm in the plane and an application to multiple robots appears in [39]. Applications of this idea to the problem of moving an elastic sheet appear in [23] and to the problem of closed kinematic chains in [27] Various sampling schemes, metrics, and local planners are compared in [1] and [1] Results using a parallel implementation are presented in [4] The paper ....

P. Svestka and M. H. Overmars, Coordinated path planning for multiple robots, Robotics and Autonomous Systems, 23 (1998), pp. 125-152.

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SVESTKA P., OVERMARS M.: Coordinated path planning for multiple robots. Robotics and Autonomous Systems 23 (1998), 125--152. c # The Eurographics Association 2004.

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P. Svestka and M. Overmars, "Coordinated path planning for multiple robots," Robotics and Autonomous Systems, vol. 23, pp. 125--152, 1998.

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P. Svestka and M.H. Overmars. Coordinated path planning for multiple robots. Robotics and Autonomous Systems, 23:125--152, 1998.

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P. Svestka, M.H. Overmars, Coordinated path planning for multiple robots, Robotics and Autonomous Systems 23 (1998), pp. 125--152.

....of PRM is that its complexity tends to be dependent on the di#culty of the path, and much less on the global complexity of the scene. In the past few years the method has been successfully applied in many motion planning problems dealing with robot arms[17] car like robots[27, 29] multiple robots[28], manipulation tasks[25] and even flexible objects[13, 18] Let us describe the application of PRM to planning camera motions in more detail. To guarantee that the camera keeps a minimal clearance to the objects in the scene, we don t consider the camera as a point but as a sphere S # (c) of ....

P. Svestka, M.H. Overmars, Coordinated path planning for multiple robots, Robotics and Autonomous Systems 23 (1998), pp. 125--152.

....using a simple local planner. See Section 2 for a more detailed description of the technique. Over the past few years the method has been successfully applied in various motion planning areas, such as articulated robots [12] mobile robots with non holonomic constraints [19, 21] multiple robots [20], and flexible objects [7, 14] The method is very efficient but, due to the probabilistic nature, it is difficult to analyse (see e.g. 10] Already in the earliest papers on probabilistic roadmap planners it was noticed that the random adding of free configurations is a bottleneck when small ....

P. vestka, M.H. Overmars, Coordinated path planning for multiple robots, Robotics and Autonomous Systems 23 (1998), pp. 125-152.

....on the diculty of the path, and much less on the global complexity of the scene or the dimension of the con guration space. In the past few years the method has been successfully applied in many motion planning problems dealing with robot arms[16] car like robots[26, 28] multiple robots[27], manipulation tasks[24] and even exible objects[11, 18] In all these cases the method is very ecient but, due to the probabilistic nature, it is dicult to analyze (see e.g. 14] In this paper I will give an overview of the probabilistic roadmap approach and indicate some of the recent ....

....degrees of freedom. For example in the situation in Fig. 3 there are 6 robot arms with a total of 36 degrees of freedom. When applying decoupled planning we rst compute the individual motions of the robots and then try to coordinate these over time. This is faster but can lead to deadlock. In [27] a solution based on PRM is proposed that lies between these two. Rather that coordinate the paths, the roadmaps themselves are coordinated, leading to a faster and probabilistically complete planner. 5 Figure 3: An example where 6 robots must plan their motions together (taken from S anchez and ....

P.  Svestka, M.H. Overmars, Coordinated path planning for multiple robots, Robotics and Autonomous Systems 23 (1998), pp. 125-152.

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P. Svestka and M. Overmars. Coordinated path planning for multiple robots. Robotics and Autonomous Systems, 23(3):125--152, Apr. 1998.

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Svestka, P. and Overmars, M. 1998. Coordinated path planning for multiple robots. Robotics and Autonomous Systems 23(3):125--152.

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P. Svestka and M. Overmars, "Coordinated path planning for multiple robots," Robotics and Autonomous Systems, vol. 23, no. 3, pp. 125--152, Apr. 1998.

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Svestka, P. and Overmars, M. 1998. Coordinated path planning for multiple robots. Robotics and Autonomous Systems 23(3):125--152.

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Svestka, P. and Overmars, M.H., "Coordinated path planning for multiple robots", Robotics and Autonomous Robots, 23(3):125-152, 1998.

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P. Svestka and M. Overmars, "Coordinated path planning for multiple robots," in Robotics and Autonomous System, 1998, pp. 125--152.

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Svestka, P., Overmars, M. H., "Coordinated Path Planning for Multiple Robots" Robotics and Autonomous Systems, Vol. 23, No. 4, pp. 125-133, 1998.

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P.  Svestka and M. Overmars. Coordinated path planning for multiple robots. Robotics and Autonomous Systems, 23:125-152, 1998.

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