8 accepted papers
This paper considers the problem of planning trajectories for a team of sensor-equipped robots to reduce uncertainty about a dynamical process. Optimizing the trade-off between information gain and energy cost (e.g., control effort, distance travelled) is desirable but leads to a non-monotone object…
In this work, we address the motion planning problem for autonomous vehicles through a new lattice planning approach, called Feedback Enhanced Lattice Planner (FELP). Existing lattice planners have two major limitations, namely the high dimensionality of the lattice and the lack of modeling of agent…
This paper proposes a novel highly scalable sampling-based planning algorithm for multi-robot active information acquisition tasks in complex environments. Active information gathering scenarios include target localization and tracking, active SLAM, surveillance, environmental monitoring and others.…
In this paper, we propose a novel Reinforcement Learning approach for solving the Active Information Acquisition problem, which requires an agent to choose a sequence of actions in order to acquire information about a process of interest using on-board sensors. The classic challenges in the informat…
In this paper, we present a learning approach to goal assignment and trajectory planning for unlabeled robots operating in 2D, obstacle-filled workspaces. More specifically, we tackle the unlabeled multi-robot motion planning problem with motion constraints as a multi-agent reinforcement learning pr…
This paper considers the problem of planning trajectories for robots equipped with sensors whose task is to track an evolving target process in the world. We focus on processes which can be represented by a Gaussian random variable, which is known to reduce the general stochastic information acquisi…
This letter considers the problem of reducing uncertainty about a physical process of interest by designing sensing trajectories for a team of robots. This active information gathering problem has applications in environmental monitoring, search and rescue, and security and surveillance. Our previou
Applications of safety, security, and rescue in robotics, such as multi-robot target tracking, involve the execution of information acquisition tasks by teams of mobile robots. However, in failure-prone or adversarial environments, robots get attacked, their communication channels get jammed, and th…