Globally Optimal Joint Search of Topology and Trajectory for Planar Linkages
This addresses the challenge of designing planar linkages for robotics, offering a method to optimize both topology and trajectory, though it is incremental as it builds on existing optimization techniques.
The paper tackles the problem of finding globally optimal topology and trajectory for planar linkages, which are useful for low-cost robots, by formulating it as a mixed-integer convex programming problem; experiments show the approach finds complex structures more efficiently and generates trajectories more accurately.
We present a method to find globally optimal topology and trajectory jointly for planar linkages. Planar linkage structures can generate complex end-effector trajectories using only a single rotational actuator, which is very useful in building low-cost robots. We address the problem of searching for the optimal topology and geometry of these structures. However, since topology changes are non-smooth and non-differentiable, conventional gradient-based searches cannot be used. We formulate this problem as a mixed-integer convex programming (MICP) problem, for which a global optimum can be found using the branch-and-bound (BB) algorithm. Compared to existing methods, our experiments show that the proposed approach finds complex linkage structures more efficiently and generates end-effector trajectories more accurately.