Geometric Design of Mechanically Reachable Surfaces J. Michael McCarthy and HaiJun Su University of California, Irvine Mathematics Seminar California State.

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Presentation transcript:

Geometric Design of Mechanically Reachable Surfaces J. Michael McCarthy and HaiJun Su University of California, Irvine Mathematics Seminar California State University, Long Beach February 27, 2004

Overview Robot manipulators and spatial mechanisms as assemblies of serial chains. The seven serial chains with reachable surfaces. The model problem: determining a sphere through four points. Counting the solutions for a set of polynomial equations. The design equations for the seven serial chains. The homotopy solution methodology for polynomial equations. POLSYS-GLP results. Other serial chains and our Synthetica software. Conclusions.

Geometric Design The kinematic structure of a robot manipulator or spatial mechanism is the network of links and joints that define its movement. The primary component of this network is the serial chain of links connected by joints. One end of the chain is the base, and the other is the end-effector. Serial Robot PUMA 560Parallel Robot HEXA The goal of geometric design is to determine the physical dimensions of a serial chain that guarantee its end-effector can achieve a specified task.

Reachable Surfaces PPS chain: Plane TS chain: Sphere RPS chain: Hyperboloid right RRS chain: Circular torus RRS chain: Torus CS chain: Circular cylinder PRS chain: Elliptic cylinder

The Model Problem Consider the problem of determining a sphere that contains four specified points. Let R be the radius of the sphere, B=(u, v, w) its center, and P=(X, Y, Z) be a general point on the sphere, then we have (X-u) 2 + (Y-v) 2 + (Z-w) 2 = R 2, or (P-B)  (P-B) = R 2 Now let P i =(X i, Y i, Z i ), i=1, 2, 3, 4 be four specified points, so we have P i  P i - 2 P i  B + B  B = R 2, i=1, 2, 3, 4 Subtract the first equation from the remaining to cancel the terms B  B and R 2, S: (P i+1  P i+1 - P i  P i ) - 2 (P i+1 - P i )  B = 0, i=1, 2, 3. This is a set of three linear equations in the parameters B=(u, v, w). There can be at most one solution, which defines the sphere that contains the four points.

Generalizing the Problem Rather than specify the points P i =(X i, Y i, Z i ), we now specify seven spatial displacements [T i ]=[A i, d i ], that define task positions for an end-effector. We now seek p=(x, y, z), B=(u, v, w) and R, such that P i = [T i ]p lie on the sphere: (X i -u) 2 + (Y i -v) 2 + (Z i -w) 2 = R 2, or ([T i ]p-B)  ([T i ]p-B) = R 2, i=1,…, 7 Subtract the first equation from the remaining to cancel the terms B  B and R 2, S: (P i+1  P i+1 - P i  P i ) - 2 (P i+1 - P i )  B = 0, i=1,…, 6, where P i = [T i ]p. This is a set of six quadratic equations in the parameters B=(u, v, w) and p=(x, y, z). There can be at most 2 6 =64 solutions. Each solution defines a TS chain that guides its end-effector through the task positions [T i ].

Counting Solutions Total degree: A system of n polynomials of degree d 1, d 2, …, d n in n variables has at most D = d 1 d 2 … d n isolated solutions. (Bezout, 1779) Monomial polytope root count (BKK theory): Proof: Bernshtein, 1975 Algorithms: Canny, 1991, Gao and Li, Multihomogeneous root count: Morgan & Sommese, 1987 General Linear Product root count: Verschelde & Haegemans, 1993, Morgan, Sommese, & Wampler, 1995

General Linear Product A polynomial system has the same number, dimension, and degree of solution components for “almost all” values of the coefficients. This means we can count solutions (roots) using a polynomial system that has the same monomial structure though different coefficients. Let denote the linear combination “a 1 u + a 2 v +a 3 w + a 4 “ where a i are generic coefficients. Then the quadratic curve Ax 2 + Bxy + Cy 2 + Dx + Ey + F = 0 can be written as the linear product =0 Example: Consider the two plane curves: C 1 : A 1 x 2 + B 1 xy + D 1 x + E 1 y + F 1 = 0, | 1 = 0 C 2 : A 2 x 2 + B 2 xy + D 2 x + E 2 y + F 1 = 0, | 2 = 0 How many solutions? Three.

The TS Serial Chain Expanding (P i+1  P i+1 - P i  P i ), we find that the quadratic terms cancel and this term actually has the form, which means the TS chain equations actually have the form: Polynomials with this structure have ( 6 3 ) = 20 roots, which means there are at most 20 TS chains that can reach the seven task positions and so on for ( 6 3 ). S: | 1 = 0, | 2 = 0, | 3 = 0, | 4 = 0, | 5 = 0, | 6 = 0. The equations for the TS chain have the monomial structure: S: - | i = 0, i=1, …, 6

Design Equations Number Task Positions Equations- degree Total Degree GLP Bound Plane (PPS) 6 5-2nd 3210 Sphere (TS) 7 6-2nd 6420 Circular Cylinder (CS) 8 7-4th 16,3842,184 Hyperboloid (RPS) th 262,1449,216 Elliptic Cylinder (PRS) rd, 9-4th 2,097,152247,968 Circular Torus (right RRS) nd, 10-4th 2,097,152868,352 Torus (RRS) th 4,194,304448,702

Solving the Design Equations The goal is to find all of the real solutions to the design equations. They are are all candidates designs. Resultant techniques can be used systems with as many as 50 roots, and eigenvalue elimination methods can extend this to as as high as 100 roots. Systems of equations with hundreds and thousands of roots require polynomial homotopy solution methods.

Polynomial Homotopy Let P(z) be the system of polynomial design equations, and we seek all the solutions z to P(z)=0. Now let Q(z) be a polynomial system that has the same monomial structure as P(z), which means we require it to have the same GLP structure. The N GLP roots of Q(z)=0 are easily computed by solving linear equations. Construct the convex combination homotopy H(, z) = (1- )Q(z) + P(z), where  [0, 1). For each root z = a j of Q(z)=0 the homotopy equation H(, z) = 0 defines a zero curve  j, j=1, …, N GLP, which is a connected component of H -1 (0). Each zero curve of H(, z) = 0 leads either to a root of P(z)=0 or a root at infinity.

Tracking Zero Curves A zero curve can be parameterized by its arc-length s, so it has the form  j = ( (s), z(s)). We seek the sequence of points y i  ( (s i ), z(s i )) along  j. Along the zero curve  j, we have H( (s), z(s))=0, therefore The matrix [J H ] = [H H z ] is the nx(n+1) matrix of partial derivatives. Notice that v = (d /ds, dz/ds) is tangent to the zero curve, and it is in the null-space of [J H ]. This allows us to estimate the next point along  j by the formula y i+1 = y i + (s i+1 - s i )v(s i ). This is essentially numerical integration of an ODE and can be solved with efficient predictor-corrector methods. Furthermore, it is well-adapted for parallel computation.

Number of Solutions Total Degree GLP Bound Number Rootscomments Plane (PPS) 3210 resultant Sphere (TS) 6420 resultant Circular Cylinder (CS) 16,3842, PHC 5+ hrs. Hyperboloid (RPS) 262,1449,2161,024 PHC 24 hrs. Elliptic Cylinder (PRS) 2,097,152247,96818,120 POLSYS-GLP 30m/8cpu Circular Torus (right RRS) 2,097,152868,35294,622 POLSYS-GLP 70m/1024cpu Torus (RRS) 4,194,304448,70242,615 POLSYS-GLP 40m/1024cpu

S YNTHETICA 2.0 These results are being integrated into computer-aided design software in the Robotics and Automation Laboratory at UCI.

Other Spatial Chains Here we have discussed seven spatial serial chains. The spatial constrained serial chains can be enumerated: There are 15 classes with an additional 35 special cases. Including permutations there are 191 chains.

Conclusions Kinematic synthesis of spatial chains provides the opportunity to invent new devices for controlled spatial movement. The seven serial chains PPS, TS, RPS, PRS, CS, right RRS, and RRS have reachable surfaces that can be shaped so that the end-effector reaches a large number of specified task positions. The general cases have a remarkably large number of solutions. Yet 90% of the paths traced by our homotopy algorithm are a waste of cpu-time. More efficient solution procedures are needed to make computer-aided- invention practical. In fact, we are beginning to consider very large scale computing that evaluates the solutions of the design equations for large number of serial chains.