4 papers
SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies
Thies Oelerich, Gerald Ebmer, Christian Hartl-Nesic +1
The emerging integration of robots into everyday life brings several major challenges. Compared to classical industrial applications, more flexibility is needed in combination with…
BoundPlanner: A convex-set-based approach to bounded manipulator trajectory planning
Thies Oelerich, Christian Hartl-Nesic, Florian Beck +1
Online trajectory planning enables robot manipulators to react quickly to changing environments or tasks. Many robot trajectory planners exist for known environments but are often…
BoundMPC: Cartesian path following with error bounds based on model predictive control in the joint space
Thies Oelerich, Florian Beck, Christian Hartl-Nesic +1
This work introduces the BoundMPC strategy, an innovative online model-predictive path-following approach for robot manipulators. This joint-space trajectory planner allows the fol…
Incremental Language Understanding for Online Motion Planning of Robot Manipulators
Mitchell Abrams, Thies Oelerich, Christian Hartl-Nesic +2
Human-robot interaction requires robots to process language incrementally, adapting their actions in real-time based on evolving speech input. Existing approaches to language-guide…