Joseph A. Cascio

Papers

Total Citations

H-Index

About

Joseph A. Cascio is a robotics and control systems researcher whose work focuses on trajectory optimization and collision avoidance for complex robotic systems. His research addresses one of the most challenging problems in robotics: enabling multiple manipulators to operate safely and efficiently in shared, obstacle-rich environments. Cascio's most recognized contribution, "Smooth Proximity Computation for Collision-Free Optimal Control of Multiple Robotic Manipulators" (2009, 11 citations), introduced an innovative framework leveraging Karush-Kuhn-Tucker conditions to compute proximity between line-swept sphere bounding volumes, providing a mathematically rigorous yet computationally practical approach to collision avoidance. This work represents a significant step forward in making multi-robot coordination feasible for real-world applications. Building on this foundation, his earlier work on optimal path planning for multi-arm, multi-link manipulators (2008, 5 citations) tackled the highly nonlinear optimal control problem of computing joint trajectories that satisfy complex performance requirements for tasks such as point-to-point positioning. Together, these contributions offer researchers and engineers principled tools for designing safer, more capable robotic systems, particularly in manufacturing and automation contexts where multiple robotic arms must collaborate in close proximity.