9 accepted papers
This paper introduces a novel motion planning algorithm designed for a team of curvature-constrained tethered robots operating on sloped 3D terrains. Our approach addresses the critical issues of tether-terrain interaction, robot stability, and tether entanglement avoidance. The study focuses on a t
This paper develop a scheduling protocol for a team of autonomous robots that operate on long-term persistent tasks. The proposed framework, called meSch, accounts for the limited battery capacity of the robots and ensures that the robots return to charge their batteries one at a time at the single
Several large-scale datasets (e.g., WikiSQL, Spider) for developing natural language interfaces to databases have recently been proposed. These datasets cover a wide breadth of domains but fall short on some essential domains, such as finance and accounting. Given that accounting databases are used…
The design of deep network architectures and training methods in computer vision has been well-explored. However in almost all cases the images have been used as provided with little exploration of pre-processing steps beyond normalization and data augmentation. Virtually all images posted on the we…
In the absence of a tether attachment mechanism that can provide infinitely large tension to the tethered robots moving on extreme planetary terrains, there is a limit on how much tension can be realistically generated or supported by the tether. In this paper, we consider a team of two robots tethe…
In this paper, a variant of hybrid A* is developed to find the shortest path for a curvature-constrained robot, that is tethered at its start position, such that the tether satisfies user-defined winding angle constraints. A variant of tangent graphs is used as an underlying graph for searching a pa…
Negation is the fundamental component in a natural language that reverses the semantic meaning of a sentence. It plays an extremely important role across a wide range of applications, yet they are underrepresented in pre-trained language models (LMs), resulting often in wrong inferences. In this wor…
Most research in the area of automatic essay grading (AEG) is geared towards scoring the essay holistically while there has also been little work done on scoring individual essay traits. In this paper, we describe a way to score essays using a multi-task learning (MTL) approach, where scoring the es…
We consider the problem of leveraging prior experience to generate roadmaps in sampling-based motion planning. A desirable roadmap is one that is sparse, allowing for fast search, with nodes spread out at key locations such that a low- cost feasible path exists. An increasingly popular approach is t…