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meco-group · Jun 19, 2024 · e27145b · e27145b
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diff --git a/_data/program.yml b/_data/program.yml
@@ -26,7 +26,7 @@ days:
         category: Theoretical
       - time: 11:15 to 12:15
         title: Tutorial on CasADi and its Opti stack
-        subtitle: How to define expressions, functions and nonlinear programs with the numerical optimization framework CasADi
+        subtitle: How to efficiently define expressions, functions and nonlinear programs with the numerical optimization framework CasADi
         category: Practical
       - time: 12:15 to 13:15
         title: Lunch break
@@ -36,7 +36,7 @@ days:
         category: Theoretical
       - time: 14:15 to 15:15
         title: Tutorial on Rockit (Part 1)
-        subtitle: How to easily specify and prototype optimal control problems
+        subtitle: How to easily specify and prototype optimal control problems using different solvers
         category: Practical
   - name: Day 2
     events:
@@ -46,21 +46,21 @@ days:
         category: General
       - time: 10:15 to 11:15
         title: Tutorial on Rockit (Part 2)
-        subtitle: How to easily specify and prototype optimal control problems
+        subtitle: How to easily specify and prototype optimal control problems using different solvers
         category: Practical
       - time: 11:15 to 11:30
         title: Introduction to nonlinear MPC
         subtitle: Short introduction on going from an optimal control problem to a model predictive controller
         category: Theoretical
       - time: 11:30 to 12:15
         title: Tutorial and interactive session on Impact (Part 1)
-        subtitle: How to easily specify, prototype and deploy MPC for robotic systems
+        subtitle: How to easily specify, prototype and deploy MPC for robotic systems in C, Python, and ROS 2
         category: Practical
       - time: 12:15 to 13:15
         title: Lunch break
       - time: 13:15 to 15:00
         title: Tutorial and interactive session on Impact (Part 2)
-        subtitle: How to easily specify, prototype and deploy MPC for robotic systems
+        subtitle: How to easily specify, prototype and deploy MPC for robotic systems in C, Python, and ROS 2
         category: Practical
       - time: 15:00 to 15:10
         title: Closing

diff --git a/index.md b/index.md
@@ -31,7 +31,7 @@ bin_picking_video_id: iULN3skmdjs
 
 ### Overview
 
-In this workshop, participants will engage in hands-on exploration of optimal control problems (OCPs) applied to motion planning and model predictive control (MPC) in autonomous robotic systems. By engaging with cutting-edge tools and techniques, participants will develop the skills necessary to navigate complex environments, optimize trajectory paths, and execute tasks with precision and efficiency in robotic systems. 
+In this workshop, participants will engage in hands-on exploration of optimal control problems (OCPs) applied to motion planning and model predictive control (MPC) in autonomous robotic systems. By engaging with cutting-edge tools and techniques, participants will develop the skills necessary to navigate complex environments, optimize trajectory paths, and execute tasks with precision and efficiency in robotic systems. Moreover, participants will learn how to swiftly deploy OCPs and MPCs in C, Python and ROS 2.
 
 To streamline the guided exercises, the workshop makes use of the free and open-source [Rockit](https://gitlab.kuleuven.be/meco-software/rockit) [1] and [Impact](https://gitlab.kuleuven.be/meco-software/impact) [2][3] software frameworks developed by the [MECO Research Team](https://www.mech.kuleuven.be/en/pma/research/meco) at KU Leuven and built on top of the numerical optimization framework [CasADi](https://github.com/casadi/casadi) [4], designed for efficient nonlinear programming.