PlaCo: a QP-based robot planning and control framework

The core principle of PlaCo is to provide a high-level interface for specifying robot control problems, while internally reformulating them into the QP formulation introduced in equation (1) expected by efficient numerical solvers. This section illustrates how common robotics problems naturally reduce to this form. First, Section III-A recalls the equivalence between least-squares objectives and the standard QP formulation. Section III-B extends this formulation to the case of multiple objectives. Section III-C discusses how to incorporate hard and soft constraints into the QP framework. Section III-D introduces integrated decision variables, which allow system dynamics to be embedded directly into the QP problem. Finally, Section III-E presents how QR factorization is used to reduce the dimensionality of the optimization problem. An usage example is provided in Appendix A to illustrate the problem specification process in PlaCo. A. From least-squares to standard QP formulation A least-squares minimization problem is formulated as min