D. E. Johnson and E. Cohen. A framework for efficient minimum distance computations. In IEEE International Conference on Robotics and Automation, pages 3678--3684, Leuven, Belgium, May 1998.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....separation distances have been extensively researched. Many are restricted to convex objects [Cameron 97, Ehmann01, Gilbert88, Lin91, Mirtich98] or are based on hierarchical bounding volume or spatial data structures that require considerable precomputation and are best suited for rigid geometry [Hubbard93, Quinlan94, Gottschalk96, Johnson98, Klosowski98]. Some algorithms handle dynamically deforming geometry by assuming that motion is expressed as a closed form function of time [Snyder93] or by using very specialized algorithms [Baraft92] In our approach, we emphasize the handling of non convex, dynamically deformable objects with no ....

....the complexity of the algorithm. We use coarse fixed height bounding volume hierarchies to achieve this balance between speed and complexity, and between CPU and graphics usage. There are many general and efficient algorithms available for localizing geometry based on bounding volume hierarchies [Gottschalk96, Hubbard93, Johnson98, Quinlan94]. However, for exact collision detection these algorithms typically perform well only on static geometry where the hierarchy can be precomputed. In order to handle dynamic deformable geometry with no precomputation, we use coarse levels for efficient trivial rejection and obtain reasonable ....

D. Johnson, E. Cohen, A Framework for Efficient Minimum Distance Computation, IEEE Conf. On Robotics and Animation, 3678-3683, 1998

....robot manipulator with a set of ellipsoids is presented in Section 4. Finally, Section 5 concludes the paper. 2. ELLIPSOID COMPUTATION FOR LINK MODELING For most practical applications in robotics and computer graphics, complex objects are generally represented as a union of simpler primitives [11]. However, the primitives should reflect a good balance between the efficiency of primitive primitive intersection detections and the number of primitives required to adequately represent the objects. For the proposed technique, the ellipsoids are selected as a basic element to represent objects. ....

....Let , y,Y) be the minimum volume n ellipsoid containing a convex polyhedron in n dimensional space. Then, the initial enclosed ellipsoid is given as , y, n 1)2Y) formed by shrinking (y,Y) from its center by a factor of (n l) to guarantee that the polyhedron contains the initial ellipsoid [11]. Therefore, the ellipsoid , y,16Y) is selected to be the initial guess for enclosed ellipsoid computation in 3 dimensional case. The regulation of the shrinking factor is based on the bisection methods. The phase terminates with a user defined error while the ellipsoid cannot extend further ....

D. E. Johnson and E. Cohen," A framework for efficient minimum distance computations," Proceedings of the IEEE Conference on Robotics and Automation, pp. 3678-3684, Leuven, Belgium, May 1998.

....98] for collision detection. For many close proximity configurations, these tight fitting BVs result in improved performance as compared to BVHs composed of spheres or AABBs. One of the commonly used algorithm for distance computation algorithm uses spheres as a BV type [Qui94] Johnson and Cohen [JC98] have used OBBs for distance computation as well. 1.1 Main Contributions In this paper, we present a new distance computation algorithm that uses hierarchies of Rectangle Swept Spheres (RSS) This BV corresponds to the set of points obtained by sweeping the center of a sphere over a 3D ....

....a pair of spherically extended polytopes (S topes) The S topes closely resemble the bounding volume shapes described in this paper. For general polygonal models, Quinlan [Qui94] proposed an algorithm using BVHs of spheres and also used them to compute approximate distance. Johnson and Cohen [JC98] used BVHs composed of oriented bounding boxes and also presented techniques to compute distance between NURBS primitives. 2.3 Spatial and Temporal Coherence In many graphics applications and simulation environments, there is usually little movement of objects between successive frames or small ....

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D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678--3683, 1998.

....distributed points on the interface of a conforming contact between smooth surfaces. Their method although slow is very powerful. The paper focuses solely on collision detection and does not address how to handle the collision response and contact evolution problems. Johnson and Cohen, in [23], present a framework for minimum distance computations between parametric surfaces. Their approach is based on a lower upper bound tree which allows them to quickly prune bounding volumes which are not involved in the minimum distance. They also show that their solution converges relatively ....

D. E. Johnson and E. Cohen. A framework for efficient minimum distance computations. In Proc. International Conference on Robotics and Automation, pages 3678--3684. IEEE, May 1998.

....collisions, intersections, and minimum separation distances have been extensively researched. Many are restricted to convex objects [2,4,6,16] or are based on hierarchical bounding volume or spatial data structures that require considerable precomputation and are best suited for rigid geometry [8,12,14,19]. Some algorithms handle dynamically deforming geometry by either having prior knowledge of motion trajectories [22] or by using very specialized algorithms [1] In our approach, we emphasize the handling of non convex, dynamically deformable objects with no precomputation or knowledge of object ....

....field. The lengths represent the distance to the boundary (right) The top level bounding boxes and their intersection used for computing the intersection points are also shown. There are many general and efficient algorithms available for localizing geometry based on bounding volume hierarchies [8,12,14,19]. However, for exact intersection testing these algorithms typically perform well only on static geometry where the hierarchy can be precomputed. In order to handle dynamic deformable geometry with no precomputation, we use coarse levels for efficient trivial rejection and to obtain reasonable ....

D. Johnson, E. Cohen, A Framework for Efficient Minimum Distance Computation, IEEE Conf. On Robotics and Animation, 3678-3683, 1998

.... systems have incorporated a haptic interface to enhance the user s ability to perform interaction tasks [CB94, Col94, FFC 95, MRF 96, MS94, OY90, RKK97, TRC 93] Researchers at the University of Utah have developed a haptic display system for virtual prototyping [NNHJ98, He97, JC98] It uses the Sarcos Dexterous Arm Master (with a 3 dof gripper) along with the Alpha 1 CAD system, dynamic simulation, and haptic interface control. Gibson [Gib95] and Avila and Sobierajski [AS96] have proposed algorithms for object manipulation including haptic interaction with volumetric ....

D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678--3683, 1998.

....designed a haptic display system for manipulating virtual mechanisms derived from a mechanical CAD design. It uses the Sarcos Dexterous Arm Master and Utah s Alpha 1 CAD system, with algorithmic support from a tracing algorithm and a minimum distance framework developed by Johnson, Cohen et al. [21,41]. They utilized a variety of algorithmic toolkits from RAPID [16] to build an OBBTree for each object, Gilbert s algorithm [15] to find distances between two OBB s and a tracing algorithm for parametric surfaces. Their system takes about 20 Gamma 150 milliseconds for models composed of 500 Gamma ....

D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678--3683, 1998.

....are identified. Because all objects have to be considered for possible contact, the global minimum distance computation is complex. The mitigating factor is that contact has not been made yet, so lower update rates are acceptable. The global minimum distance calculation is broken into two steps [9]. Most NURBS surfaces can be quickly eliminated from consideration by using bounding boxes. This first step makes use of the convex hull property of the control mesh, which forms a natural polygonal bounding box for the NURBS surface (Figure 3) In the second step, the closest point is found to ....

D. E. Johnson and E. Cohen. A framework for efficient minimum distance computations. In Proc. IEEE Intl. Conf. Robotics and Automation, Leuven, Belgium, May 1998.

.... systems have incorporated a haptic interface to enhance the user s ability to perform interaction tasks [CB94, Col94, FFC 95, MRF 96, MS94, OY90, RKK97, TRC 93] Researchers at the University of Utah have developed a haptic display system for virtual prototyping [NNHJ98, He97, JC98] It uses the Sarcos Dexterous Arm Master (with a 3 dof gripper) along with the Alpha 1 CAD system, dynamic simulation, and haptic interface control. Gibson [Gib95] and Avila and Sobierajski [AS96] have proposed algorithms for object manipulation including haptic interaction with volumetric ....

D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678--3683, 1998.

....a pair of spherically extended polytopes (S topes) The S topes closely resemble the bounding volume shapes described in this paper. For general polygonal models, Quinlan [Qui94] proposed an algorithm using BVHs of spheres and also used them to compute approximate distance. Johnson and Cohen [JC98] used BVHs composed of oriented bounding boxes and also presented techniques to compute distance between NURBS primitives. For parametric or implicit surfaces whose motion can be expressed as a closed form function of time, Snyder et al. Sea93] have presented algorithms based on interval ....

....two simple techniques for improving the pruning of the BVTT by causing ffl to approach ffi quickly. These two techniques are called priority directed search and triangle caching. 6. 1 Priority Directed Search Instead of traversing the BVTT as a strictly depth first or breadth first search [JC98] we use a priority queue to schedule which of the pending tests to perform next. We prioritize the pending BVTT visits according to the distance: the closest pending BV pair is given a higher priority and visited next. The goal is to guide the search process so that ffl approaches the ffi value ....

[Article contains additional citation context not shown here]

D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678--3683, 1998.

....designed a haptic display system for manipulating virtual mechanisms derived from a mechanical CAD design. It uses the Sarcos Dexterous Arm Master and Utah s Alpha 1 CAD system, with algorithmic support from a tracing algorithm and a minimum distance framework developed by Johnson, Cohen et al. [36, 19]. They utilized a variety of algorithmic toolkits from RAPID [15] to build an OBBTree for each object, Gilbert s algorithm [14] to find distances between two OBB s and a tracing algorithm for parametric surfaces. Their system takes about 20 Gamma 150 milliseconds for models composed of 500 Gamma ....

D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678--3683, 1998.

....bounding volume hierarchies. These include OBBTree [GLM96] k dops [KHM 96] Boxtree [BCG 96] Axis aligned bounding boxes [CLMP95] ShellTree [KGL 98] Spheretrees [Hub93] S bounds [Cam91] etc. Bounding volume hierarchies have also been used for global distance computation [Qui94, JC98, Got98] The resulting algorithms and system provide real time performance for relatively small models composed of hundreds of thousands of polygons. Furthermore, all the hierarchical approaches are memory intensive, requiring many hundreds of bytes per triangle on average. 2.2 Managing Large ....

D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678-- 3683, 1998.

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D. E. Johnson and E. Cohen, "A framework for efficient minimum distance computations," in IEEE International Conference on Robotics and Automation, May 1998, pp. 3678--3684, leuven, Belgium. 12

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Johnson, D. E. and Cohen, E., "A framework for efficient minimum distance computations," Proc. IEEE Intl. Conf. Robotics & Automation, Leuven, Belgium, May 16-21, 1998, pp. 3678-3684.

....VxWorks (Wind River Systems, Inc. and ControlShell (Real Time Innovations, Inc. Instead of Ethernet commu nication between the workstation and SBCs, we em ploy the Myrinet (Myricom, Inc. for consistent lowlatency and high bandwidth communications. Global minimum distance calculations [6] deter mine where the haptic interface is about to contact a model, and is performed at a rate of a few Hz; hence it is suitable for the workstation. Surface contact and tracing is accomplished at kHz rates on the SBCs [13] A key point in these geometric computations is the direct use of NURBS ....

Johnson, D.E., and Cohen, E., "A framework for efficient minimum distance computations," in IEEE Intl. Conf. Robotics Automation, Leuven,

....spatialized normal cone hierarchies to find the minimum distance between models. Our solution finds all the local minima between models as well as the usual global minimum distance. ################ Minimum distance computations have been used in robotics [9] computer graphics [10] and haptics [11]. Distance measures are important because they are predictive they warn of potential events, such as contact, in advance. Almost all minimum distance literature, especially for polygonal models, treats the problem as primarily an Euclidean one. Approaches typically partition the model into a ....

....spatial bounding volume. Nodes of the hierarchy may be pruned by obtaining a lower bound on the distance to the contained geometry and comparing that distance to an upper bound on the minimum distance obtained through a depth first descent in the hierarchy [12,8] or a sample point on the surface [11]. The primary research thrust in this area has focused on methods for quickly determining the lower bound on the distance at a node. A different approach has been found in work on sculptured surfaces, such as B splines [13,10] Often a local solution to the minimum distance is desired, rather ....

#Johnson, David E. and Cohen, Elaine, A framework for efficient minimum distance computations, Proc. IEEE Intl. Conf. Robotics & Automation, Leuven, Belgium, May 16-21, 1998, pp. 3678-3684.

....j 1 ) See section 4.4.3 below for more details. Note that restricting the search space for minimum point distance searches has the positive side effect of decreasing the computation necessary for these searches. The algorithm makes use of the operation find closest point on curve to point. See [41, 40] for recent work in this area. 4.4.2 Bounding a Metric Metric 1 of section 4.1.3 is used for d(f; g) Thus d(c 1 (t) c 2 (r i (t) sup t kc 1 (t) Gamma c 2 (r i (t) k F(c 1 (t) c 2 (r i (t) Establishing a bound for this choice of distance metric d is accomplished using the ....

Johnson, D. E., and Cohen, E. A framework for efficient minimum distance computations. In Proceedings of the 1998 IEEE International Conference on Robotics & Automation (Leuven, Belgium, May 16-21 1998), pp. 3678--3684.

....has not been Figure 2: Depiction of a user employing a haptic interface to interact with a virtual brake assembly. Figure 3: Closest point from a fintertip to a trimmed NURBS model. made yet, so lower update rates are acceptable. The global minimum distance calculation is broken into two steps [3]. 1. Bounding boxes. Most NURBS surfaces can be quickly eliminated from consideration by using bounding boxes. Taking advantage of coherence between time steps can speed up this computation [5] 2. Nodal mapping. The control mesh forms a convex hull for its NURBS surface (Figure 4) Once the ....

D.E. Johnson and E. Cohen, "A framework for efficient minimum distance computations," Proc. IEEE Intl. Conf. Robotics & Automation, pp. 3678-3684, 1998.

....(5) which correctly describes that the line between the closest points is normal to each surface. This system has been solved with a search over the four dimensional parameter space [Snyder, 1995] with global, high dimensional resultant methods [Lin, 1994] and Euclidean space bounding methods [Johnson, 1998a] Note that in haptic applications, we are often interested in the local solution to distance. Using a local solution constrains the force computation to a continuous solution, similar to a God object [Zilles, 1995] or virtual proxy [Ruspini, 1997] as used in polygonal methods (see Fig.2) ....

....shape, yet have additional control points. These additional control points converge quadratically to the surface as the refinement is increased. We can exploit these properties to prune away portions of surfaces that are further away than some threshold, refine the remaining portions, and repeat [Johnson, 1998a] Remaining areas may be used to find approximate minimum distances to initiate faster, local, Newton methods. 3.2 Local Minimum Distance The local minimum distance phase uses Newton methods to quickly update the minimum distance between portions of the model. We use a reformulated extremal ....

Johnson, D. E., and Cohen, E., " A framework for efficient minimum distance computations," Proc. IEEE Intl. Conf. Robotics & Automation, Leuven, Belgium, May 16-21, 1998, pp. 3678-3684.

....0 (5) which correctly describes that the line between the closest points is normal to each surface. This system has been solved with a search over the four dimensional parameter space [Snyder, 1995] with global, high dimensional resultant methods [Lin, 1994] and Euclidean space bounding methods [Johnson, 1998a] Note that in haptic applications, we are often interested in the local solution to distance. Using a local solution constrains the force computation to a continuous solution, similar to a God object [Zilles, 1995] or virtual proxy [Ruspini, 1997] as used in polygonal methods (see Fig.2) The ....

....shape, yet have additional control points. These additional control points converge quadratically to the surface as the refinement is increased. We can exploit these properties to prune away portions of surfaces that are further away than some threshold, refine the remaining portions, and repeat [Johnson, 1998a] Remaining areas may be used to find approximate minimum distances to initiate faster, local, Newton methods. 3.2 Local Minimum Distance The local minimum distance phase uses Newton methods to quickly update the minimum distance between portions of the model. We use a reformulated extremal ....

Johnson, D. E., and Cohen, E., " A framework for efficient minimum distance computations," Proc. IEEE Intl. Conf. Robotics & Automation, Leuven, Belgium, May 16-21, 1998, pp. 3678-3684.

....representations. In tests, we find using this approach can more than double the speed of a non coherent approach. 1 Introduction In this paper we describe a novel time coherence scheme for minimum distance computations which provides a several time speed up over a previous noncoherent approach [9]. We are interested in minimum distance as a predictor of contact in a haptic assembly project [8] Others have used minimum distance computations for robotic path planning [2] collision avoidance [10] and collision detection [5] 1] For complex concave geometries a useful approach to compute ....

.... distance computations for robotic path planning [2] collision avoidance [10] and collision detection [5] 1] For complex concave geometries a useful approach to compute the minimum distance between models has been to surround the models in the scene with hierarchies of bounding volumes [14][9]. These volumes can be pruned by establishing and refining an upper bound on the minimum distance between two models, then removing bounding volumes that have lower bounds on their distance greater than the current upper bound. As the algorithm descends the bounding volume hierarchies, the lower ....

[Article contains additional citation context not shown here]

Johnson, David E. and Cohen, Elaine, "A framework for efficient minimum distance computations," Proc. IEEE Intl. Conf. Robotics & Automation, Leuven, Belgium, May 16-21, 1998, pp. 3678-3684.

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D. E. Johnson and E. Cohen. A framework for efficient minimum distance computations. In IEEE International Conference on Robotics and Automation, pages 3678--3684, Leuven, Belgium, May 1998.

No context found.

D. Johnson and E. Cohen, "A framework for efficient minimum distance computations," in Proc. of the IEEE Int. Conf. on Robotics and Automation, 1998, pp. 3678--3684.

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D. Johnson and E. Cohen. A framework for efficient minimum distance computation. IEEE Conference on Robotics and Automation, pages 3678-- 3683, 1998.

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