Low-level motion planning techniques must be combined with high-level task planning formalisms in order to generate realistic plans that can be carried out by humans and robots. Previous attempts to integrate these two planning formalisms mostly used either Classical Planning or HTN Planning. Recently, we developed Hierarchical Goal Networks (HGNs), a new hierarchical planning formalism that co...

One difficulty with existing theoretical work on HTN planning is that it does not address some of the planning constructs that are commonly used in HTN planners for practical applications. Although such constructs can make it difficult to ensure the soundness and completeness of HTN planning, they are important because they can greatly improve the efficiency of planning in practice. In this pap...

Hierarchies are the most common structure used to understand the world better. In galaxies, for instance, multiple-star systems are organised in a hierarchical system. Then, governmental and company organisations are structured using a hierarchy, while the Internet, which is used on a daily basis, has a space of domain names arranged hierarchically. Since Artificial Intelligence (AI) planning p...

The ability to plan for multi-step manipulation tasks in unseen situations is crucial future home robots. But collecting sufficient experience data end-to-end learning often infeasible the real world, as deploying robots many environments can be prohibitively expensive. On other hand, large-scale scene understanding datasets contain diverse and rich semantic geometric information. how leverage ...

Abstract Task planning is a crucial component in facilitating robot multi-task manipulations. Language-based task methods offer practicality receiving commands from humans real-life scenarios and require only low-cost labeled data. However, existing often rely on sequence models for planning, which primarily focus mapping language to sequences of sub-tasks while neglecting the knowledge about t...

Prospection, the act of predicting the consequences of many possible futures, is intrinsic to human planning and action, and may even be at the root of consciousness. Surprisingly, this idea has been explored comparatively little in robotics. In this work, we propose a neural network architecture and associated planning algorithm that (1) learns a representation of the world useful for generati...

This paper aims to discuss the requirements of safe and smooth trajectory planning of transporter mobile robots to perform non-prehensile object manipulation task. In non-prehensile approach, the robot and the object must keep their grasp-less contact during manipulation task. To this end, dynamic grasp concept is employed for a box manipulation task and corresponding conditions are obtained an...