M. Pesavento
Papers
1
Total Citations
7
H-Index
1
About
Dr. M. Pesavento’s research advances the frontier of multi-robot coordination and cooperative manipulation, with a particular focus on enabling complex physical interactions through intelligent control. Their most cited work, “Model Predictive Control for Cooperative Transportation with Feasibility-Aware Policy” (2021, 7 citations), introduces a novel MPC framework that ensures safe, feasible trajectory planning for teams of robots jointly transporting large payloads. By embedding feasibility constraints directly into the control policy, this contribution addresses a critical bottleneck in real-world multi-robot deployment—balancing coordination, dynamics, and obstacle avoidance. Beyond transportation, Pesavento’s broader research spans distributed optimization, networked control systems, and autonomy, with an emphasis on scalable, real-time decision-making. Their work is recognized for bridging theoretical control guarantees with practical robotic applications, offering clear pathways for teams of agents to collaborate under uncertainty. With a growing citation footprint and a focus on actionable solutions, Pesavento’s research is shaping how future multi-robot systems will tackle shared physical tasks in logistics, manufacturing, and disaster response.
Research Focus
Key Achievements
Top Papers
- 1