14 accepted papers
Despite their promise to perform complex reasoning, large language models (LLMs) have been shown to have limited effectiveness in end-to-end planning. This has inspired an intriguing question: if these models cannot plan well, can they still contribute to the planning framework as a helpful plan eva…
Autonomous mobile robots (e.g., warehouse logistics robots) often need to traverse complex, obstacle-rich, and changing environments to reach multiple fixed goals (e.g., ware-house shelves). Traditional motion planners need to calculate the entire multi-goal path from scratch in response to changes
We present a novel approach to learning-augmented, long-horizon navigation under uncertainty in large-scale environments in which considering the robot dynamics is essential for informing good behavior. Our approach tightly integrates sampling-based motion planning, which computes dynamically feasib…
When facing a new motion-planning problem, most motion planners solve it from scratch, e.g., via sampling and exploration or starting optimization from a straight-line path. However, most motion planners have to experience a variety of planning problems throughout their lifetimes, which are yet to b…
Multi-goal motion planning requires a robot to plan collision-free and dynamically-feasible motions to reach multiple goals, often in unstructured, obstacle-rich environments. This is challenging due to the complex dependencies between navigation and high-level reasoning, requiring the robot to expl…
As the future of autonomous underwater vehicle (AUV) deployments tends to multi-vehicle systems, new approaches in coordination and control are needed. In this work, we consider the problem of simultaneous survey and inspection where one vehicle dynamically discovers objects while another vehicle mu…
While sampling-based approaches have made significant progress, motion planning with dynamics still poses significant challenges as the planner has to generate not only collision-free but also dynamically-feasible trajectories that enable the robot to reach its goal. To improve the efficiency of sam…
This letter studies the problem of data collection where an autonomous underwater vehicle (AUV) is required to inspect several goals while staying within the communication range of an unmanned surface vehicle (USV) moving along a predefined path. A reward is associated with each inspected goal, and,
This paper studies the multi-robot motion-planning problem with unlabeled goals where n robots have to reach m goals. The proposed approach also takes into account the underlying dynamics of each robot to produce dynamically-feasible trajectories that enable the robots to reach all the goals while a…
This letter combines sampling-based motion planning with multi-agent search to efficiently solve challenging multi-robot motion-planning problems with dynamics. This idea has shown promise in prior work that developed a centralized approach to expand a motion tree in the composite state space of all
Robots used for inspection, package deliveries, moving of goods, and other logistics operations are often required to visit certain locations within specified time bounds. This gives rise to a challenging problem as it requires not only planning collision-free and dynamically feasible motions but al
This paper studies the problem of autonomous data collection where an underwater vehicle is required to reach several target regions within a specified time limit. The proposed approach takes into account the vehicle dynamics, the time-varying ocean currents, and the obstacles in the region in order
This paper presents an approach that combines geometry processing with motion planning to enable a robot to efficiently navigate in unstructured environments. The proposed approach relies on a novel oversegmentation method to produce a decomposition of the free space into a set of connected regions.
This paper develops an efficient approach to generate a collision-free and dynamically feasible trajectory that enables a robotic vehicle to inspect the entire workspace or a subset consisting of one or several regions. The approach makes it possible to specify constraints on the order in which the