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Related papers: Optimal and Stable Multi-Layer Object Rearrangemen…

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Object Rearrangement is to move objects from an initial state to a goal state. Here, we focus on a more practical setting in object rearrangement, i.e., rearranging objects from shuffled layouts to a normative target distribution without…

Machine Learning · Computer Science 2023-01-18 Mingdong Wu , Fangwei Zhong , Yulong Xia , Hao Dong

We investigate the utility of employing multiple buffers in solving a class of rearrangement problems with pick-n-swap manipulation primitives. In this problem, objects stored randomly in a lattice are to be sorted using a robot arm with…

Robotics · Computer Science 2023-02-20 Kai Gao , Jingjin Yu

Today's complex robotic designs comprise in some cases a large number of degrees of freedom, enabling for multi-objective task resolution (e.g., humanoid robots or aerial manipulators). This paper tackles the stability problem of a…

We present an optimization-based framework for rearranging indoor furniture to accommodate human-robot co-activities better. The rearrangement aims to afford sufficient accessible space for robot activities without compromising everyday…

Robotics · Computer Science 2023-03-13 Weiqi Wang , Zihang Zhao , Ziyuan Jiao , Yixin Zhu , Song-Chun Zhu , Hangxin Liu

Object rearrangement is the problem of enabling a robot to identify the correct object placement in a complex environment. Prior work on object rearrangement has explored a diverse set of techniques for following user instructions to…

Robotics · Computer Science 2023-10-03 Kartik Ramachandruni , Max Zuo , Sonia Chernova

We present a novel framework for addressing the challenges of multi-Agent planning and formation control within intricate and dynamic environments. This framework transforms the Multi-Agent Path Finding (MAPF) problem into a Multi-Agent…

Robotics · Computer Science 2024-05-14 Zong Chen , Songyuan Fa , Yiqun Li

Many exciting robotic applications require multiple robots with many degrees of freedom, such as manipulators, to coordinate their motion in a shared workspace. Discovering high-quality paths in such scenarios can be achieved, in principle,…

Robotics · Computer Science 2019-03-05 Rahul Shome , Kiril Solovey , Andrew Dobson , Dan Halperin , Kostas E. Bekris

Extrinsic manipulation, a technique that enables robots to leverage extrinsic resources for object manipulation, presents practical yet challenging scenarios. Particularly in the context of extrinsic manipulation on a supporting plane,…

Robotics · Computer Science 2023-07-13 Peng Xu , Zhiyuan Chen , Jiankun Wang , Max Q. -H. Meng

Generalizable manipulation requires that robots be able to interact with novel objects and environment. This requirement makes manipulation extremely challenging as a robot has to reason about complex frictional interactions with…

Robotics · Computer Science 2024-07-08 Yuki Shirai , Devesh K. Jha , Arvind U. Raghunathan

The growing deployment of human-robot collaborative processes in several industrial applications, such as handling, welding, and assembly, unfolds the pursuit of systems which are able to manage large heterogeneous teams and, at the same…

Robotics · Computer Science 2023-09-26 Edoardo Lamon , Fabio Fusaro , Elena De Momi , Arash Ajoudani

Reorienting objects by using supports is a practical yet challenging manipulation task. Owing to the intricate geometry of objects and the constrained feasible motions of the robot, multiple manipulation steps are required for object…

Robotics · Computer Science 2023-08-30 Peng Xu , Hu Cheng , Jiankun Wang , Max Q. -H. Meng

This paper presents a manipulation planning algorithm for robots to reorient objects. It automatically finds a sequence of robot motion that manipulates and prepares an object for specific tasks. Examples of the preparatory manipulation…

Robotics · Computer Science 2018-12-11 Weiwei Wan , Kensuke Harada , Fumio Kanehiro

This paper is a follow-up to a previous work where we defined and generated the set of all possible compromises of multilevel multiobjective linear programming problems (ML-MOLPP). In this paper, we introduce a new algorithm to solve…

Optimization and Control · Mathematics 2023-10-10 Mustapha Kaci , Sonia Radjef

We study the problem of robotic stacking with objects of complex geometry. We propose a challenging and diverse set of such objects that was carefully designed to require strategies beyond a simple "pick-and-place" solution. Our method is a…

Task-oriented object grasping and rearrangement are critical skills for robots to accomplish different real-world manipulation tasks. However, they remain challenging due to partial observations of the objects and shape variations in…

Robotics · Computer Science 2026-03-06 Yichen Cai , Jianfeng Gao , Christoph Pohl , Tamim Asfour

We focus on the problem of rearranging a set of objects with a team of car-like robot pushers built using off-the-shelf components. Maintaining control of pushed objects while avoiding collisions in a tight space demands highly coordinated…

We consider the Multi-Robot Task Allocation (MRTA) problem that aims to optimize an assignment of multiple robots to multiple tasks in challenging environments which are with densely populated obstacles and narrow passages. In such…

Robotics · Computer Science 2025-06-10 Seabin Lee , Joonyeol Sim , Changjoo Nam

The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning…

Multi-robot assembly systems are becoming increasingly appealing in manufacturing due to their ability to automatically, flexibly, and quickly construct desired structural designs. However, effectively planning for these systems in a manner…

Motion planning trajectories for a multi-limbed robot to climb up walls requires a unique combination of constraints on torque, contact force, and posture. This paper focuses on motion planning for one particular setup wherein a six-legged…

Robotics · Computer Science 2023-08-16 Xuan Lin , Jingwen Zhang , Junjie Shen , Gabriel Fernandez , Dennis W Hong