1 citations · 2 across the 6 of their papers we have counts for
6 papers
Affordance-Based Manipulation Planning with Text Goals and Sim-to-Real Generalisation via Real-to-Sim Image Conversion
Solvi Arnold, Rin Karashima, Tadashi Adachi +2
We present a manipulation planning system based on affordance recognition and action effect prediction. The system reasons through possible futures in visual form, and evaluates ca…
A Dataset and Benchmark for Robotic Cloth Unfolding Grasp Selection: The ICRA 2024 Cloth Competition
Victor-Louis De Gusseme, Thomas Lips, Remko Proesmans +59
Robotic cloth manipulation suffers from a lack of standardized benchmarks and shared datasets for evaluating and comparing different approaches. To address this, we created a bench…
Flow-Lenia.png: Evolving Multi-Scale Complexity by Means of Compression
Tadashi Adachi, Solvi Arnold, Takafumi Mochizuki +1
We propose a fitness measure quantifying multi-scale complexity for cellular automaton states, using compressibility as a proxy for complexity. The use of compressibility is ground…
Breaching the Bottleneck: Evolutionary Transition from Reward-Driven Learning to Reward-Agnostic Domain-Adapted Learning in Neuromodulated Neural Nets
Solvi Arnold, Reiji Suzuki, Takaya Arita +1
Advanced biological intelligence learns efficiently from an information-rich stream of stimulus information, even when feedback on behaviour quality is sparse or absent. Such learn…
Recognising Affordances in Predicted Futures to Plan with Consideration of Non-canonical Affordance Effects
Solvi Arnold, Mami Kuroishi, Tadashi Adachi +1
We propose a novel system for action sequence planning based on a combination of affordance recognition and a neural forward model predicting the effects of affordance execution. B…
Cloth Manipulation Planning on Basis of Mesh Representations with Incomplete Domain Knowledge and Voxel-to-Mesh Estimation
Solvi Arnold, Daisuke Tanaka, Kimitoshi Yamazaki
We consider the problem of open-goal planning for robotic cloth manipulation. Core of our system is a neural network trained as a forward model of cloth behaviour under manipulatio…