E.G. Gilbert, D.W. Johnson, S.S. Keerthi, A fast procedure for computing the distance between complex objects in three-dimensional space, IEEE Journal of Robotics and Automation 4 (2) (1988) 193--203.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....can be used to design dynamic detection routines. The basic idea is that information about the distance and dynamic states of all objects provides lower bounds on the earliest time of collision. The problem of distance computation has been well studied in the past for polyhedral objects, e.g. [5, 8, 3], but only little effort has spent on objects with curved surfaces [11] There are two reasons for this situation. First, a polygonal representation is not considered a true restriction since real objects can be approximated arbitrarily precisely by a polyhedron. The second reason is the fact that ....

E. Gilbert, D. Johnson, and S. Keerthi. A fast procedure for computing the distance between complex objects in 3d space. IEEE Journ. of Robot. Autom., 4(2):193--203, 1988.

....any of the vertices of the four cuboids. Experiments show that the method is very fast so that we can assume the computation takes O(1) time. This method is extendable to convex objects, except that the computation of the distance from a point to a convex polytopes with m faces, costs O(log m) [5]. To compute the shortest distance from a point p to an arbitrary convex polytope P , we can compute the distance from p to a simplex whose vertices are vertices of the convex polytope. This value is a upper bound on the shortest distance since the simplex is entirely inside the polytope. The ....

D. W. J. E. G. Gilbert and S. S. Keerthi. A fast procedure for computing the distance between complex objects in three-dimensional space. IEEE Trans. Robotics and Automation, 4(2):193--203, April 1988.

....of the trees trunks and those of the remaining characters, plus the virtual walls that materialize the limits of the scene. Then an improved version of the algorithm of Gilbert Johnson Keerthi (GJK) is used to compute the shortest distances between the characters and these possible obstacles ([4, 14]) and we finally keep the nearest one intersecting the character s sensor range (see figure 5) 5.2. Reactive avoidance behaviour The rationale of the decision process is to transform the sensor information (d, #) into the motor command (v, #) where v is the desired linear velocity and # the ....

E. Gilbert, D. Johnson, and S. Keerthi. A fast procedure for computing the distance between complex objects in three dimensional space. IEEE Journal of Robotics and Automation, 4, 1988.

....the 7,136 tested frames, which is quite unacceptable for most applications. The last column shows that the number of miss reports of the GJK method is reduced to 1.7 of the 7,136 tested frames, with 4,376 vertices being used for polyhedral approximation; its running time is roughly doubled, to 0. 958 seconds, in this case. In general, increased running time is needed for the GJK method, due to the increased number of vertices for polyhedral approximation, to trade for higher accuracy. In fact, this tradeoff between accuracy and efficiency is intrinsic to any collision detection methods based ....

....accuracy. In fact, this tradeoff between accuracy and efficiency is intrinsic to any collision detection methods based on polyhedral approximation. Hence, according to these tests, our method is not only ex VERTICES 488 1460 4376 BBOX INT 7136 7136 7136 COLLIDE 787 787 787 Running time of 0. 543 0.541 0.544 EECD (secs) Running time of GJK (secs) 0.563 0.605 0.958 for 10000 frames MISS GJK 787 482 122 11.0 6.8 1.7 VERTICES: the number of vertices used by GJK for polyhedral approximation; BBOX INT: the number of frames with intersecting bounding boxes; COLLIDE: the number ....

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E.G. Gilbert, D.W. Johnson, and S.S. Keerthi. A fast procedure for computing the distance between complex objects in three dimensional space. IEEE Transactions on Robotics and Automation, vol. 4(2), pp. 193-203, 1988.

....WORK Many collision detection methods for various purposes have been developed in the past [LG98] Some of them are employed and adapted for the particular requirements of cloth modelling. Collision detection for convex polyhedra has been extensively studied and is based on the GJK Algorithm [GJK88], Lin Canny Algorithm [LC91] or V Clip [Mir98] Non convex objects can be decomposed into convex parts [EL01; Ehm] R trees [Gut84] provide the theoretical basics for bounding volume hierarchies, which are mostly used to generate hierarchical representations of complex meshes. In addition, ....

....velocity cone (figure 6) which is also used to detect temporal coherence during the detection process. A velocity cone is computed similarly to a normal cone. but also polygonal primitives, we compute the closest points between convex polygons with an adapted implementation of the GJK algorithm [GJK88]. We do not restrict the proximity detection to the simple particle face test, since it is not sufficient for an accurate collision detection and limits cloth mod elling to high resolution meshes (figure 7) Textilx, N Penetration Figure 7: Particle based collision detection is inexact and ....

E.G. Gilbert, D. W. Johnson, and S.S. Keerthi. A Fast Procedure for Computing the Distance Between Complex Objects in ThreeDimensional Space. IEEE Journal of Robotics and Automation, 4(2), 1988.

....Whenever two colliding hierarchy leaves have been found, the distance between each pair of primitives is calculated, and candidate pairs are detected and passed to the collision response. We compute the closest points between convex polygons with an adapted implementation of the GJK algorithm [10], because the primitives have (b) Figure 5: Recursion using binary trees (a) and quadtrees respectively (b) not necessarily to be triangles. Since we can stop the hierarchy setup at a certain node size to save memory, the leaves can represent more than one polygon. In order to handle multiple ....

E.G. Gilbert, D. W. Johnson, and S.S. Keerthi. A Fast Procedure for Computing the Distance Between Complex Objects in Three-Dimensional Space. IEEE Journal of Robotics and Automa- tion, 4(2), 1988.

....Work Many collision detection methods for various pur poses have been developed in the past [22] Some of them are employed and adapted for the particular requirements of cloth modelling. Collision detection for convex polyhedra has been extensively studied and is based on the GJK Algorithm [12], Lin Canny Algorithm [21] or VClip [24] Non convex objects can be decomposed into convex parts [10, 9] R trees [14] provide the theoretical basics for bounding volume hierar chies [3, la, 20, 19, 16, 26] which are mostly used to generate hierarchical representations of complex meshes. In ....

....found, the distance between each pair of faces is calculated, and candidate pairs are detected and passed to the collision response. To handle not only triangles but also polygonal primitives, we compute the closest points between convex polygons with an adapted implementation of the GJK algorithm [12]. We do not restrict the proximity detection to the simple particle face test, since it is not sufficient for an accurate collision detection and limits cloth modelling to high resolution meshes (figure 7) Penetration Textilx i gdbJct I Figure 7: Particle based collision detection is ....

E.G. Gilbert, D. W. Johnson, and S.S. Keerthi. A Fast Procedure for Computing the Distance Between Complex Objects in Three- Dimensional Space. IEEE Journal of Robotics [23] and Automation, 4(2), 1988.

....algorithm showing a way to speed up overlap tests between AABBs and thus aligning AABB to OBB performance for rigid models. For deformable models, AABB are even faster to build and to update. The SOLID library also exploits an enhanced version of the Gilbert, Johnson and Keerthi (GJK) algorithm [10], which computes distance between two convex polytopes using Minkowski di#erence and convex optimization techniques. The SOLID improvement over earlier GJK [10, 2] is discussed in [23] along with the obtained performance, robustness, and versatility. Finally, for convex hull computation SOLID ....

....faster to build and to update. The SOLID library also exploits an enhanced version of the Gilbert, Johnson and Keerthi (GJK) algorithm [10] which computes distance between two convex polytopes using Minkowski di#erence and convex optimization techniques. The SOLID improvement over earlier GJK [10, 2] is discussed in [23] along with the obtained performance, robustness, and versatility. Finally, for convex hull computation SOLID relies on the Qhull library. PQP [16, 17] PQP employs a top down strategy to create a hierarchy of Rectangle Swept Spheres (RSS) from a polygon soup model. A RSS is ....

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E. Gilbert, D. Johnson, and S. Keerthi. A fast procedure for computing the distance between complex objects in three dimensional space. IEEE Journal of Robotics and Automation, 4(2):193--203, 1988.

....e goodness, expansiveness, and path clearance. While e goodness allows us to study how well a probabilistic roadmap covers F, expansiveness and path clearance allow us to compare the connectedness of the roadmap to that of F. Computer Science Department, Stanford University, Stanford, CA 94305, USA. ICompurer Science Department, Rice University, Houston, TX 77005, USA. 1.1 INTRODUCTION The path planning problem can be formulated as follows: Given: A geometric and kinematic model of a rigid or articulated object, called the robot, A geometric model of the obstacles in the ....

....this approach only uses the implicit representation of F that is provided by a function clist(q) which computes the distance be tween the robot at configuration q and the obstacles in the Euclidean space 5k 2 or 5k a. This function admits several reasonably efficient implementations (e.g. 8, 9, 15, 22, 23, 24, 27, 30] The planner samples at random. Using clis; it retains the configurations in free space as milestones and, for every pair of milestones, it checks that a simple path between them (usually, the straight line segment in ) is collision free. The result is a graph R called ....

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E.G. Gilbert, D.W.Johhson, and S.S. Keerthi. A Fast Procedure for Computing the Distance Between Complex Robots in Three-Dimensional Space. IEEE Tr. on Robotics and Automation, 4:193-203, 1988.

....NO PATH answer. The cost of computing an explicit representation of F in a high dimensional space is prohibitive. Instead, a PRM uses the implicit representation of F provided by ds, which only computes distances in 5 2 or 5 a and admits several reasonably efficient implementa tions (e.g. [7, 8, 12, 18, 19, 20, 22, 25]) In this paper we often use simple illustrative examples of 2 D free spaces, which could easily be handled by other planning techniques. Keep in mind that in practical problems, it is often not realistic to explicitly represent F. 3 Other Sampling Strategies The planner in [5] uses a partially ....

....obstacles. To be more specific, let the robot be made of p rigid bodies L, Lp. Let ti be the shortest translation that Li must undergo be fore it touches an obstacle. The distance dist(q) is min= ti . As we mentioned in Section 2, a num ber of techniques have been proposed to implement dist [7, 8, 12, 18, 19, 20, 22, 25]. To be usable by new roadmap, the function dist(q) should be extended to compute the (negated) penetra tion distance of the robot into the obstacles at configurations where q F. Then, q G F if and only if clst(q) 5. Consistently with the above definition of clst(q) when q G F, we can define ....

E.G. Gilbert, D.W.Johhson, and S.S. Keerthi. A Fast Procedure for Computing the Distance Between Complex Robots in Three-Dimensional Space. IEEE Tr. Rob. and Aut., 4:193-203, 1988.

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E.G. Gilbert, D.W. Johnson, S.S. Keerthi, A fast procedure for computing the distance between complex objects in three-dimensional space, IEEE Journal of Robotics and Automation 4 (2) (1988) 193--203.

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E. G. Gilbert, D. W. Johnson, and S. Keerthi. A fast procedure for computing the distance between complex objects in three dimensional space. IEEE Journal of Robotics and Automattion, 4(2):193--203, April 1988.

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E. G. Gilbert, D. W. Johnson, and S. S. Keerthi. A fast procedure for computing the distance between complex objects in threedimensional space. IEEE Transactions on Robotics and Automation, 4(2):193--203, Apr. 1988.

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E. Gilbert, D. Johnson, and S. Keerthi. A fast procedure for computing the distance between complex objects in three-dimensional space. IEEE Journal of Robotics and Automation, 4(2):193--203, April 1988.

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E. Gilbert, D. Johnson, and S. Keerthi, "A fast procedure for computing the distance between complex objects in three-dimensional space," IEEE J. of Robotics and Automation, vol. 4, no. 1, pp. 193--203, 1998.

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E.G.Gilbert, D.W.Johnson and S.S.Keerthi, \A Fast Procedure for Computing the Distance Between Complex Objects in Three Dimensional Space," IEEE Journal of Robotics and Automation, 4(2), 1988.

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E. G. Gilbert, D. W. Johnson, and S. S. Keerth. A fast procedure for computing the distance between complex objects in three-dimensional space. IEEE J. of Robot. & Autom., RA-4(2):193--203, Apr 1988.

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E. G. Gilbert, D. W. Johnson, and S. S. Keerthi. A fast procedure for computing the distance between complex objects. Internat. J. Robot. Autom., 4(2):193--203, 1988.

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E. G. Gilbert, D. W. Johnson, and S. S. Keerthi, "A fast procedure for computing the distance between complex objects in three-dimensional space," IEEE J. Robot. Automat., vol. 4, pp. 193--203, Apr. 1988.

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GILBERT, E. G., JOHNSON, D., AND KEERTHI, S. A fast procedure for computing the distance between complex objects in threedimensional space. IEEE Journal Of Robotics and Automation,2 (April 1988), 193--203.

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E. G. Gilbert, D. W. Johnson, and S. Keerthi. A fast procedure for computing the distance between complex objects in three dimensional space. IEEE Journal of Robotics and Automattion, 4(2):193--203, April 1988.

No context found.

E.G. Gilbert, D.W. Johnson, S.S. Keerthi, A fast procedure for computing the distance between complex objects in three-dimensional space, IEEE Journal of Robotics and Automation 4 (2) (1988) 193--203.

No context found.

Gilbert, E.G. and Johnson, D.W. and Keerthi, S.S. A fast procedure for computing the distance between complex objects in threedimensional space. IEEE Journal of Robotics and Automation. vol 4. No 2. pp 193-203. April, 1988.

No context found.

E. G. Gilbert, D. W. Johnson, and S. S. Keerthi. A fast procedure for computing the distance between complex objects in three-dimensional space. IEEE Journal of Robotics and Automation, 4(2):193--203, Apr. 1988.

No context found.

E.G.Gilbert, D.W. Johnson, S. Keerthi. "A fast procedure for computing the distance between complex objects in three dimensional space", IEEE Journal of Robotics and Automation 4, 2, pp. 193--203 (Apr. 1988).

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