J. de la Casa Cardenas

About

J. de la Casa Cardenas is a robotics researcher specializing in model predictive control (MPC) and visual servoing for anthropomorphic robotic manipulators. Their work focuses on enabling robots to operate safely and precisely in unstructured and constrained environments. A key contribution is the development of a model predictive position/force control framework for robotic arms, which allows seamless transitions between free-space motion and contact tasks without the need for controller switching—a critical advance for tasks in unknown or restricted spaces. This work has garnered 11 citations. De la Casa Cardenas also pioneered the integration of Time-of-Flight (ToF) 3D cameras with predictive control strategies for visual servoing. Their 2013 paper on visual predictive control using a ToF camera (8 citations) introduced a novel eye-to-hand configuration that leverages depth information to handle workspace constraints and target tracking in unstructured settings. A subsequent paper refined this approach for object tracking tasks. Collectively, their research advances the robustness and autonomy of robotic manipulators, bridging vision and control for real-world applications.

Research Focus

Key Achievements

Top Papers

1. 1
   Model predictive position/force control of an anthropomorphic robotic arm

   11 citations · 2015
2. 2
   Visual Predictive Control of Robot Manipulators Using a 3D ToF Camera

   8 citations · 2013
3. 3
   Position predictive control of an anthropomorphic robotic arm using a time-of-flight camera

   2 citations · 2014

Key Collaborators

Contact & Links