4 citations · 4 across the 5 of their papers we have counts for
14 papers · 1 filter
Online state vector reduction during model predictive control with gradient-based trajectory optimisation
David Russell, Rafael Papallas, Mehmet Dogar
Non-prehensile manipulation in high-dimensional systems is challenging for a variety of reasons. One of the main reasons is the computationally long planning times that come with a…
Robust Physics-Based Manipulation by Interleaving Open and Closed-Loop Execution
Wisdom C. Agboh, Mehmet R. Dogar
We present a planning and control framework for physics-based manipulation under uncertainty. The key idea is to interleave robust open-loop execution with closed-loop control. We…
Occlusion-Aware Search for Object Retrieval in Clutter
Wissam Bejjani, Wisdom C. Agboh, Mehmet R. Dogar +1
We address the manipulation task of retrieving a target object from a cluttered shelf. When the target object is hidden, the robot must search through the clutter for retrieving it…
Human-Guided Planner for Non-Prehensile Manipulation
Rafael Papallas, Mehmet R. Dogar
We present a human-guided planner for non-prehensile manipulation in clutter. Most recent approaches to manipulation in clutter employs randomized planning, however, the problem re…
Human-like Planning for Reaching in Cluttered Environments
Mohamed Hasan, Matthew Warburton, Wisdom C. Agboh +6
Humans, in comparison to robots, are remarkably adept at reaching for objects in cluttered environments. The best existing robot planners are based on random sampling of configurat…
Parareal with a Learned Coarse Model for Robotic Manipulation
Wisdom Agboh, Oliver Grainger, Daniel Ruprecht +1
A key component of many robotics model-based planning and control algorithms is physics predictions, that is, forecasting a sequence of states given an initial state and a sequence…