7 citations · 9 across the 10 of their papers we have counts for
8 papers · 1 filter
Building Generalization Into Behavior Generation Via Adaptive Compositions of Regularities
Aravind Battaje, Malte Bernhard, Vito Mengers +1
Generalization in robotics requires prior knowledge about how the world is structured, yet this structure changes from one situation to the next. This paper investigates the propos…
World-Task Factorization for Robot Learning
Eduardo Sebastián, Adrian Pfisterer, Vito Mengers +2
Robot learning must produce policies that generalize to new combinations of constraints, teammates, and environments. To achieve this, we must structurally factor the policy, which…
Resolving Conflicts Where and When They Arise: Reactive Composition of Multi-Goal Behavior
Vito Mengers, Oliver Brock
Multi-goal robotic tasks are commonly delegated to planning, because reactive control is prone to local minima when objectives conflict. We show that many such failures stem from s…
A Mechanistic Model for Collective Motion from Sensorimotor Regularities
Vito Mengers, Bao Duc Cao, Oliver Brock
Collective behavior in animals has long been modeled through self-propelled particle models, which reproduce striking group-level phenomena through abstract interaction forces. Yet…
No Plan, Yet Human: A Reactive Robotics Model Predicts Human Planning Failures on a Clinical Task
Michael Migacev, Vito Mengers, Antonia Köngeter +1
Understanding why some sequential planning problems are harder than others requires models that go beyond average performance. They should capture the specific pattern of which pro…
Coupled Particle Filters for Robust Affordance Estimation
Patrick Lowin, Vito Mengers, Oliver Brock
Robotic affordance estimation is challenging due to visual, geometric, and semantic ambiguities in sensory input. We propose a method that disambiguates these signals using two cou…
A Helping (Human) Hand in Kinematic Structure Estimation
Adrian Pfisterer, Xing Li, Vito Mengers +1
Visual uncertainties such as occlusions, lack of texture, and noise present significant challenges in obtaining accurate kinematic models for safe robotic manipulation. We introduc…
No Plan but Everything Under Control: Robustly Solving Sequential Tasks with Dynamically Composed Gradient Descent
Vito Mengers, Oliver Brock
We introduce a novel gradient-based approach for solving sequential tasks by dynamically adjusting the underlying myopic potential field in response to feedback and the world's reg…