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To economically deploy robotic manipulators the programming and execution of robot motions must be swift. To this end, we propose a novel, constraint-based method to intuitively specify sequential manipulation tasks and to compute…

Robotics · Computer Science 2022-08-22 Mun Seng Phoon , Philipp S. Schmitt , Georg v. Wichert

Stable dynamical systems are a flexible tool to plan robotic motions in real-time. In the robotic literature, dynamical system motions are typically planned without considering possible limitations in the robot's workspace. This work…

Robotics · Computer Science 2020-03-26 Matteo Saveriano , Dongheui Lee

We introduce a novel strategy for multi-robot sorting of waste objects using Reinforcement Learning. Our focus lies on finding optimal picking strategies that facilitate an effective coordination of a multi-robot system, subject to…

Robotics · Computer Science 2024-09-23 Tizian Jermann , Hendrik Kolvenbach , Fidel Esquivel Estay , Koen Kramer , Marco Hutter

In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights have associated…

Robotics · Computer Science 2015-03-13 Alphan Ulusoy , Stephen L. Smith , Calin Belta

We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi-robot…

Robotics · Computer Science 2022-11-15 Daniel Tihanyi , Yimeng Lu , Orcun Karaca , Maryam Kamgarpour

Trained humans exhibit highly agile spatial skills, enabling them to operate vehicles with complex dynamics in demanding tasks and conditions. Prior work shows that humans achieve this performance by using strategies such as satisficing,…

Systems and Control · Electrical Eng. & Systems 2020-04-28 Andrew Feit , Bérénice Mettler

Path Planning and target searching in a three-dimensional environment is a challenging task in the field of robotics. It is an optimization problem as the path from source to destination has to be optimal. This paper aims to generate a…

Artificial Intelligence · Computer Science 2019-11-07 Devansh Verma , Priyansh Saxena , Ritu Tiwari

Robotic-based compact storage and retrieval systems provide high-density storage in distribution center and warehouse applications. In the system, items are stored in bins, and the bins are organized inside a three-dimensional grid. Robots…

Robotics · Computer Science 2023-12-12 Anni Yue , Stephen L. Smith

Many robots are not equipped with a manipulator and many objects are not suitable for prehensile manipulation (such as large boxes and cylinders). In these cases, pushing is a simple yet effective non-prehensile skill for robots to interact…

Robotics · Computer Science 2025-11-21 Zili Tang , Ying Zhang , Meng Guo

Motion planning is a mature area of research in robotics with many well-established methods based on optimization or sampling the state space, suitable for solving kinematic motion planning. However, when dynamic motions under constraints…

In this paper, we present a motion planning framework for multi-modal vehicle dynamics. Our proposed algorithm employs transcription of the optimization objective function, vehicle dynamics, and state and control constraints into sparse…

Robotics · Computer Science 2021-07-07 L. Lao Beyer , N. Balabanska , E. Tal , S. Karaman

Automation of logistic processes is essential to improve productivity and reduce costs. In this context, intelligent warehouses are becoming a key to logistic systems thanks to their ability of optimizing transportation tasks and,…

Sampling-based motion planning algorithms have been continuously developed for more than two decades. Apart from mobile robots, they are also widely used in manipulator motion planning. Hence, these methods play a key role in collaborative…

Robotics · Computer Science 2023-07-13 Carl Gaebert , Sascha Kaden , Benjamin Fischer , Ulrike Thomas

This paper presents a sampling-based method for optimal motion planning in non-holonomic systems in the absence of known cost functions. It uses the principle of learning through experience to deduce the cost-to-go of regions within the…

Robotics · Computer Science 2021-01-08 Nahas Pareekutty , Francis James , Balaraman Ravindran , Suril V. Shah

This paper presents a distributed multi-robot printing method which utilizes an optimization approach to decompose and allocate a printing task to a group of mobile robots. The motivation for this problem is to minimize the printing time of…

We address multi-robot geometric task-and-motion planning (MR-GTAMP) problems in synchronous, monotone setups. The goal of the MR-GTAMP problem is to move objects with multiple robots to goal regions in the presence of other movable…

Motion planning in the presence of multiple dynamic obstacles is an important research problem from the perspective of autonomous vehicles as well as space-constrained multi-robot work environment. In this paper, we address the motion…

Systems and Control · Electrical Eng. & Systems 2019-12-30 Trishant Roy , Anindya Harchowdhury , Leena Vachhani

This work considers a Motion Planning Problem with Dynamic Obstacles (MPDO) in 2D that requires finding a minimum-arrival-time collision-free trajectory for a point robot between its start and goal locations amid dynamic obstacles moving…

Robotics · Computer Science 2022-06-03 Zhongqiang Ren , Sivakumar Rathinam , Howie Choset

We consider the problem of reconfiguring a two-dimensional connected grid arrangement of passive building blocks from a start configuration to a goal configuration, using a single active robot that can move on the tiles, remove individual…

We study the problem of sequential task assignment and collision-free routing for large teams of robots in applications with inter-task precedence constraints (e.g., task $A$ and task $B$ must both be completed before task $C$ may begin).…

Robotics · Computer Science 2020-06-17 Kyle Brown , Oriana Peltzer , Martin A. Sehr , Mac Schwager , Mykel J. Kochenderfer