Task and motion planning (TAMP) integrates high-level task planning and low-level motion
planning to equip robots with the autonomy to effectively reason over long-horizon, dynamic …

In a world designed for legs, quadrupeds, bipeds, and humanoids have the opportunity to
impact emerging robotics applications from logistics, to agriculture, to home assistance. The …

Optimization is a ubiquitous modeling tool and is often deployed in settings which
repeatedly solve similar instances of the same problem. Amortized optimization methods …

We propose a hybrid model predictive control algorithm, consensus complementarity
control, for systems that make and break contact with their environment. Many state-of-the …

We introduce a prescriptive machine learning approach to speed up the process of solving
mixed-integer convex optimization (MICO) problems. We solve multiple optimization …

We propose an approach based on machine learning to solve two-stage linear adaptive
robust optimization (ARO) problems with binary here-and-now variables and polyhedral …

Electric motors are widely used in robots but waste energy in many applications. We
introduce an elastic energy-recycling actuator that maintains the versatility of motors while …

Trajectory optimization in robotics poses a challenging non-convex problem due to complex
dynamics and environmental settings. Traditional numerical optimization methods are time …

Abstract Mixed integer Model Predictive Control (MPC) problems arise in the operation of
systems where discrete and continuous decisions must be taken simultaneously to …

Mixed‐integer model predictive control (MI‐MPC) can be a powerful tool for controlling
hybrid systems. In case of a linear‐quadratic objective in combination with linear or …