12 accepted papers
Tethered robots find widespread application in underwater and disaster recovery missions. This study focuses on the coverage path planning (CPP) problem for a tethered robot, considering cable constraints and the presence of forbidden areas in the environment. We propose adapting the spanning tree-
This paper introduces a novel distributed approach for forming UAV-based multi-hop relay networks by adapting traditional flocking models to create relay chains between remote points. Our method modifies the standard flocking paradigm by incorporating dynamic agent roles, allowing UAVs to self-organ
Implicit representations such as Neural Radiance Fields (NeRF) allow to map color, density and semantics in a 3D scene through a continuous neural function. However, these models typically require manual and careful human data collection for training. This paper addresses the problem of active explo
How to coordinate multiple robots moving in modifiable cluttered environments? In this paper, we introduce the multi-robot version of the NAMO problem (Navigation Among Movable Obstacles). In MR-NAMO, robots must not only plan for the possibility of displacing obstacles as needed to facilitate their…
Successfully addressing a wide variety of tasks is a core ability of autonomous agents requiring flexibly adapting the underlying decision-making strategies and as we argue in this work also adapting the perception modules. An analogical argument would be the human visual system which uses top-down…
Understanding and mapping a new environment are core abilities of any autonomously navigating agent. While classical robotics usually estimates maps in a stand-alone manner with SLAM variants, which maintain a topological or metric representation, end-to-end learning of navigation keeps some form of…
This paper addresses a path planning problem for a fleet of Unmanned Aerial Vehicles (UAVs) that uses both prior information and online gathered data to efficiently inspect large surfaces such as ship hulls and water tanks. UAVs can detect corrosion patches and other defects on the surface from low-…
In the context of visual navigation, the capacity to map a novel environment is necessary for an agent to exploit its observation history in the considered place and efficiently reach known goals. This ability can be associated with spatial rea-soning, where an agent is able to perceive spatial rela…
In this paper, we study existing flocking models and propose extensions to improve their abilities to deal with environments having obstacles impacting the communication quality. Often depicted as robust systems, there is yet a lack of understanding how flocking models compare and how they are impac…
We train an agent to navigate in 3D environments using a hierarchical strategy including a high-level graph based planner and a local policy. Our main contribution is a data driven learning based approach for planning under uncertainty in topological maps, requiring an estimate of shortest paths in…
This paper addresses the problem of exploring unknown terrains with a fleet of cooperating aerial vehicles. We present a novel decentralized approach which alternates gradient-free stochastic optimization and a frontier-based approach. Our method allows each robot to generate its trajectory based on…
In ambient intelligence, pressure sensing can be used for detecting and recognizing objects based on their load profile. This paper presents a pressure scanning technique that improves weight-based object recognition, by adding information about the surface of the object in contact with the floor. T…