17 accepted papers
This paper introduces the BOW Planner, a scalable motion planning algorithm designed to navigate robots through complex environments using constrained Bayesian optimization (CBO). Unlike traditional methods, which often struggle with kinodynamic constraints such as velocity and acceleration limits, …
Numerical weather prediction (NWP) models remain the cornerstone of atmospheric sciences. Yet, deep learning (DL) is challenging this paradigm by its ability to capture intricate spatio-temporal patterns and deliver ultra-fast predictions. Analogous to the foundation models (e.g., ChatGPT) in natura
This letter presents an energy-efficient multi-robot coverage path planning (MRCPP) framework for large, nonconvex Regions of Interest (ROI) containing obstacles and no-fly zones (NFZ). Existing minimum-energy coverage planning algorithms utilize meta-heuristic boustrophedon workspace decomposition.
We address multi-robot motion planning under Signal Temporal Logic (STL) specifications with kinodynamic constraints. Exact approaches face scalability bottlenecks and limited adaptability, while conventional sampling-based methods require excessive samples to construct optimal trajectories. We prop…
Diffusion-based trajectory planners can synthesize rich, multimodal robot motions from demonstrations, but their iterative denoising makes online planning and control prohibitively slow. Existing accelerations either modify the sampler or compress the network–sacrificing plan quality or requiring re…
Robots equipped with rich sensor suites can localize reliably in partially-observable environments---but powering every sensor continuously is wasteful and often infeasible. Belief-space planners address this by propagating pose-belief covariance through analytic models and switching sensors heurist…
Scalar field features such as extrema, contours, and saddle points are essential for applications in environmental monitoring, search and rescue, and resource exploration. Traditional navigation methods often rely on predefined trajectories, leading to inefficient and resource-intensive mapping. Thi
Predicting the near-term behavior of a reactive agent is crucial in many robotic scenarios, yet remains challenging when observations of that agent are sparse or intermittent. Vision-Language Models (VLMs) offer a promising avenue by integrating textual domain knowledge with visual cues, but their o
Effective data collection in collaborative information-gathering systems relies heavily on maintaining uninterrupted connectivity. Yet, real-world communication disruptions often pose challenges to information-gathering processes. To address this issue, we introduce a novel method —a limited communi
We present an incremental scalable motion planning algorithm for finding maximally informative trajectories for decentralized mobile robots. These robots are deployed to observe an unknown spatial field, where the informativeness of observations is specified as a density function. Existing works tha
There has been significant interest in recent years in the utility and implementation of autonomous underwater and surface vehicles (AUVs and ASVs) for persistent surveillance of the ocean. Example studies include the dynamics of physical phenomena, e.g., ocean fronts, temperature and salinity profi
Communication is one of the most popular and efficient means of multi-robot coordination. Due to potential real-world constraints, such as limited bandwidth and contested scenarios, a communication strategy requiring to send, for example, all n bits of an environment representation might not be feas…
We consider the problem of multiple robots that must cooperate within a shared environment, but which wish to limit the information they disclose during their coordination efforts. Specifically, we examine the problems of privacy-preserving rendezvous and persistent monitoring. In the former, the ro…
Traditional environmental and structural monitoring often uses static sensor networks deployed at predetermined locations or mobile robots that use a rastering technique for area coverage. These methods rely on the operators making assumptions about the nature of the unknown field that is being meas…
Robot localization is the problem of determining a robot's pose in an environment, typically within a given map or a similar representation. Different methods have been proposed to address this localization problem for robots with limited sensing. In this letter, we present a localization method for
In this paper, we solve the problem of relay robot placement in multi-robot missions to establish or enhance communication between a static operator and a number of remote units in an environment with known obstacles. We study the hardness of two different relay placement problems: 1) a chain format…
Collisions between moving machinery and human workers in construction job sites are one of the main sources of fatalities and accidents during the execution of construction projects. In this paper, we present a methodology to identify and assess construction project plan dangers before their executi…