Inverse Dynamics Trajectory Optimization for Contact-Implicit Model Predictive Control by Vince Kurtz, Alejandro Castro, Aykut Özgün Önol, and Hai Lin. https ...

Abstract: Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems ...

Abstract: This paper investigates the issue of event-triggered distributed model predictive control for coupled nonlinear systems with additive disturbances. Specifically, this paper proposes two ...

BMPC is a model-based reinforcement learning algorithm built on TD-MPC2’s world model, designed to enhance policy learning through expert iteration. BMPC leverages Model Predictive Control (MPC) to ...

With AI finding security bugs faster than humans can patch them, your safest bet is building bulletproof infrastructure from ...

The artificially intelligent systems being integrated into the vehicles of 2026 are evolving faster than they can be applied.

Smart manufacturers know industrial AI is only as effective as the data behind it. Discover how to build an AI-ready data ...

China is pioneering a distinct AI approach, prioritizing systems for real-time urban, industrial, and logistical coordination ...

The future of equitable AI in community health centers will be measured by how effectively we are able to demand partnership ...

Dr. Alex Fedoseyev, Director of Research at Ultra Quantum Inc., explores a new paradigm for turbulence modelling known as the ...

New AI model enables ChemPass AI for Ag™ to identify and prioritize antifungal molecules with a higher probability of biological success at early discovery stages REHOVOT, Israel, July 15, 2026 ...

Growing consumer demand for protein poses a crucial question for dairy producers: How can they meet that demand without adding costly new production capacity? For a growing number, the answer is to ...