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Position-aware relation learning for RGB-thermal salient object detection
Salient object detection (SOD) is an important task in computer vision that aims to identify
visually conspicuous regions in images. RGB-Thermal SOD combines two spectra to …
visually conspicuous regions in images. RGB-Thermal SOD combines two spectra to …
Decentralized probabilistic multi-robot collision avoidance using buffered uncertainty-aware Voronoi cells
In this paper, we present a decentralized and communication-free collision avoidance
approach for multi-robot systems that accounts for both robot localization and sensing …
approach for multi-robot systems that accounts for both robot localization and sensing …
Non-gaussian risk bounded trajectory optimization for stochastic nonlinear systems in uncertain environments
We address the risk bounded trajectory optimization problem of stochastic nonlinear robotic
systems. More precisely, we consider the motion planning problem in which the robot has …
systems. More precisely, we consider the motion planning problem in which the robot has …
Convex risk bounded continuous-time trajectory planning in uncertain nonconvex environments
In this paper, we address the trajectory planning problem in uncertain nonconvex static and
dynamic environments that contain obstacles with probabilistic location, size, and geometry …
dynamic environments that contain obstacles with probabilistic location, size, and geometry …
Learning-based risk-bounded path planning under environmental uncertainty
Building a general and efficient path planning framework in uncertain nonconvex
environments is challenging due to the safety constraints and complex configuration …
environments is challenging due to the safety constraints and complex configuration …
Stochastic implicit neural signed distance functions for safe motion planning under sensing uncertainty
Motion planning under sensing uncertainty is critical for robots in unstructured environments,
to guarantee safety for both the robot and any nearby humans. Most work on planning under …
to guarantee safety for both the robot and any nearby humans. Most work on planning under …
Robust optimization-based motion planning for high-DOF robots under sensing uncertainty
Motion planning for high degree-of-freedom (DOF) robots is challenging, especially when
acting in complex environments under sensing uncertainty. While there is significant work on …
acting in complex environments under sensing uncertainty. While there is significant work on …
Human-guided motion planning in partially observable environments
Motion planning is a core problem in robotics, with a range of existing methods aimed to
address its diverse set of challenges. However, most existing methods rely on complete …
address its diverse set of challenges. However, most existing methods rely on complete …
Convex risk-bounded continuous-time trajectory planning and tube design in uncertain nonconvex environments
In this paper, we address the trajectory planning problem in uncertain nonconvex static and
dynamic environments that contain obstacles with probabilistic location, size, and geometry …
dynamic environments that contain obstacles with probabilistic location, size, and geometry …
Real-Time Tube-Based Non-Gaussian Risk Bounded Motion Planning for Stochastic Nonlinear Systems in Uncertain Environments via Motion Primitives
We consider the motion planning problem for stochastic nonlinear systems in uncertain
environments. More precisely, in this problem the robot has stochastic nonlinear dynamics …
environments. More precisely, in this problem the robot has stochastic nonlinear dynamics …