4 citations · 6 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
Chemotaxis Based Virtual Fence for Swarm Robots in Unbounded Environments
Simon O. Obute, Mehmet R. Dogar, Jordan H. Boyle
This paper presents a novel swarm robotics application of chemotaxis behaviour observed in microorganisms. This approach was used to cause exploration robots to return to a work ar…
Simple Swarm Foraging Algorithm Based on Gradient Computation
Simon O. Obute, Mehmet R. Dogar, Jordan H. Boyle
Swarm foraging is a common test case application for multi-robot systems. In this paper we present a novel algorithm for controlling swarm robots with limited communication range a…
Non-Prehensile Manipulation in Clutter with Human-In-The-Loop
Rafael Papallas, Mehmet R. Dogar
We propose a human-operator guided planning approach to pushing-based manipulation in clutter. Most recent approaches to manipulation in clutter employs randomized planning. The pr…
Learning Physics-Based Manipulation in Clutter: Combining Image-Based Generalization and Look-Ahead Planning
Wissam Bejjani, Mehmet R. Dogar, Matteo Leonetti
Physics-based manipulation in clutter involves complex interaction between multiple objects. In this paper, we consider the problem of learning, from interaction in a physics simul…