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Luis Moreno

6 accepted papers

2025

Coordination of Learned Decoupled Dual-Arm Tasks through Gaussian Belief Propagation

IROS 2025

Robotic manipulation can involves multiple manipulators to complete a task. In those cases, the complexity of performing the task in a coordinated manner increases, requiring coordinated planning while avoiding collisions between robots and environmental elements. For these challenges, we propose a

Cited by 2SourcecodeScholar
2025

Industry 6.0: New Generation of Industry driven by Generative AI and Swarm of Heterogeneous Robots

IROS 2025

This paper presents the concept of Industry 6.0, which introduces the world’s first fully automated production system that autonomously handles the entire product design and manufacturing process based on user-provided natural language descriptions. By leveraging generative AI, the system automates

Cited by 13SourceScholar
2023

CollisionGP: Gaussian Process-Based Collision Checking for Robot Motion Planning

RA-L 2023

Collision checking is the primitive operation of motion planning that consumes most time. Machine learning algorithms have proven to accelerate collision checking. We propose CollisionGP, a Gaussian process-based algorithm for modeling a robot's configuration space and query collision checks. Collis

Cited by 13SourceScholar
2015

An asymptotically-optimal sampling-based algorithm for Bi-directional motion planning

IROS 2015poster

Bi-directional search is a widely used strategy to increase the success and convergence rates of sampling-based motion planning algorithms. Yet, few results are available that merge both bi-directional search and asymptotic optimality into existing optimal planners, such as PRM*, RRT*, and FMT*. The…

Cited by 61SourceScholar