14 accepted papers
In situations where a delivery robot shares limited resources with people who are incidentally copresent in the same space, its behavior affects both those individuals and customers awaiting delivery. In this paper, we refer to such individuals as incidentally copresent persons (InCops). Most prior
We propose CARE (Collision Avoidance via Repulsive Estimation) for improving the robustness of learning-based visual navigation methods. Recently, visual navigation models, particularly foundation models, have demonstrated promising performance by generating viable trajectories using only RGB images…
We tackle the challenges of decentralized multi-robot navigation in environments with nonconvex obstacles, where complete environmental knowledge is unavailable. While reactive methods like Artificial Potential Field (APF) offer simplicity and efficiency, they suffer from local minima, causing robot
We propose a hybrid approach for decentralized multi-robot navigation that ensures both safety and deadlock prevention. Building on a standard control formulation, we add a lightweight deadlock prevention mechanism by forming temporary "roundabouts" (circular reference paths). Each robot relies only
We address the motion planning problem for multiple robotic manipulators in packed environments where shared workspace can result in goal positions occupied or blocked by other robots unless those other robots move away to make the goal positions free. While planning in a coupled configuration space
We present a coordination method for multiple mobile manipulators to sort objects in clutter. We consider the object rearrangement problem in which the objects must be sorted into different groups in a particular order. In clutter, the order constraints could not be easily satisfied since some objec…
We consider the problem of retrieving a target object from a confined space by two robotic manipulators where overhand grasps are not allowed. If other movable obstacles occlude the target, more than one object should be relocated to clear the path to reach the target object. With two robots, the re…
We consider the problem of rearranging objects in a cluttered and confined space using a robotic manipulator. The goal is to retrieve a target object from the clutter where the target is occluded by other objects. In situations where overhand grasps are not allowed, the robot needs to remove some ob…
We propose a tree search-based planning algorithm for a robot manipulator to rearrange objects and grasp a target in a dense space. We consider environments where tasks cannot be completed with prehensile planning only. As assuming that a manipulator is only allowed to grasp from the top, we aim to…
This paper presents a task and motion planning (TAMP) framework for a robotic manipulator in order to retrieve a target object from clutter. We consider a configuration of objects in a confined space with a high density so no collision-free path to the target exists. The robot must relocate some obj…
We present an algorithm determining where to relocate objects inside a cluttered and confined space while rearranging objects to retrieve a target object. Although methods that decide what to remove have been proposed, planning for the placement of removed objects inside a workspace has not received…
We present an algorithm that produces a plan for relocating obstacles in order to grasp a target in clutter by a robotic manipulator without collisions. We consider configurations where objects are densely populated in a constrained and confined space. Thus, there exists no collision-free path for t…
We consider multi-robot teams operating in uncertain dynamic settings where the costs used for computing task-allocations are not known exactly. In such cases, the desire to minimize the team's expected cost might need to be curtailed if, in doing so, the risk that results is intolerable. We describ
We address the problem of finding the optimal assignment of tasks to a team of robots when the associated costs may vary, which arises when robots deal with uncertain or dynamic situations. We detail how to compute a sensitivity analysis that characterizes how much costs may change before optimality…