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GraspMixer: Hybrid of Contact Surface Sampling and Grasp Feature Mixing for Grasp Synthesis

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 10920-10936页

作者： Lee, Hojun Toner, Tyler Tilbury, Dawn M. Barton, Kira Purdue Univ Dept Mech Engn W Lafayette IN 47906 USA Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA Univ Michigan Robot Dept Ann Arbor MI 48109 USA Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

The capability of robots to rapidly adapt to new tasks without extensive reprogramming offers significant flexibility in reconfiguration of manufacturing processes to cope with unforeseen events. In modern manufacturing environments where numerous hardware and software systems exchange data with each other to perform a myriad of tasks, modularizing sub-systems and reusing commonly available information like product CAD models can increase robustness and efficiency of the reconfiguration. Yet, current approaches for robotic grasping tend to focus on standalone vision-based learning that often require either retraining to adapt to new object categories or massive dataset not available in manufacturing environments, making generalization challenging. This paper addresses the problem of exploiting available information, like CAD models, in manufacturing settings to efficiently generate a tractable set of grasps for known rigid objects, which can be directly applied to a wide class of robotic manipulations. In order to quickly produce diverse grasp configurations for arbitrary geometric models, we present GraspMixer, a combination of (1) an efficient offline sampler that utilizes specifications of a parallel-jaw gripper, and (2) a mapping function that fuses multiple features of a grasp to output a binary quality metric. During evaluation using physics-based simulations, a robotic gripper successfully executes 92.9% of all grasp configurations for 12 novel objects selected by GraspMixer. Among five different grasp sampling methods, GraspMixer also achieves the highest grasp success rate when performing table-top single object grasping under object pose uncertainty. The computation of this offline pipeline takes less than 1.0 minutes for each object without GPU hardware acceleration, which is comparable to or outperforms most of the benchmarks in the evaluation. Importantly, our framework exhibits impressive simulation-to-reality adaptation, achieving over 95% grasp succe

关键词： Solid modeling Robots Grippers Manufacturing Computational modeling Grasping Three-dimensional displays Measurement Analytical models Adaptation models Robotic grasping smart manufacturing offline algorithm heuristic-based sampling learning-based quality estimation

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Optimal online and offline algorithms for robot-assisted restoration of barrier coverage

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DISCRETE APPLIED MATHEMATICS 2020年 285卷 650-662页

作者： Czyzowicz, J. Kranakis, E. Krizanc, D. Narayanan, L. Opatrny, J. Univ Quebec Outaouais Dep Informat Gatineau PQ Canada Carleton Univ Sch Comp Sci Ottawa ON Canada Wesleyan Univ Dept Math & Comp Sci Middletown CT USA Concordia Univ Dept Comp Sci & Software Eng Montreal PQ Canada

Assume that n wireless sensors are initially arbitrarily distributed on a line segment barrier. Each sensor is said to cover the portion of the barrier that intersects with its sensing area. Owing to incorrect initial position, or the death of some of the sensors, the barrier is not completely covered by the sensors. We employ a mobile robot to move the sensors to final positions on the barrier such that barrier coverage is guaranteed. We seek algorithms that minimize the length of the robot's trajectory, since this allows the restoration of barrier coverage as soon as possible. We give an optimal linear-time offline algorithm that gives a minimum-length trajectory for a robot that starts at one end of the barrier and achieves the restoration of barrier coverage. We also study two different online models: one in which the online robot does not know the length of the barrier in advance, and the other in which the online robot knows the length of the barrier. For the case when the online robot does not know the length of the barrier, we prove a tight bound of 3/2 on the competitive ratio, and we give a tight lower bound of 5/4 on the competitive ratio in the other case. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Optimal trajectory offline algorithm Online algorithm Barrier coverage Competitive ratio Wireless sensors

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Obtaining online approximation algorithms for facility dispersion from offline algorithms

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NETWORKS 2006年第4期47卷 206-217页

作者： Rosenkrantz, Daniel J. Tayi, Giri K. Ravi, S. S. SUNY Albany Dept Comp Sci Albany NY 12222 USA SUNY Albany Sch Business Dept Management Sci & Informat Syst Albany NY 12222 USA

Facility dispersion problems arise in the context of placing obnoxious facilities and retail outlets. In the off line version of such a problem, the input consists of a complete graph on n nodes, a nonnegative weight (distance) for each edge, and the number k <= n of facilities to be placed. The goal is to choose a facility placement consisting of k nodes so as to maximize a given measure of the distances among the facilities. Here, we consider an online version of the problem where the value of k is not known apriori;instead, requests for facilities arrive one at a time. It is also required that previously placed facilities cannot be moved or eliminated. Our main result is that for any objective that satisfies two properties, namely monotonicity and graceful degradation, any off line approximation algorithm with a performance guarantee p can be used to develop an algorithm with competitive ratio c rho for the online version, where c is a constant independent of the problem instance. Objectives for which our result applies include the average edge weight and average weight of a star subgraph. The result holds even when the edge weights do not satisfy the triangle inequality. We also identify dispersion objectives for which the offline and online versions have different behaviors when only one of the above two properties Is satisfied. (C) 2006 Wiley Periodicals, Inc.

关键词： facility dispersion offline algorithm online algorithm approximation ratio competitive ratio

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Optimal Online and offline algorithms for Finding Longest and Shortest Subsequences with Length and Sum. Constraints

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2010年第2期E93D卷 250-256页

作者： Kim, Sung Kwon Chung Ang Univ Sch Comp Sci & Engn Seoul 156756 South Korea

In this paper, we address the following problems: Given a sequence A of n real numbers, and four parameters I, J, X and Y with I <= J and X <= Y, find the longest (or shortest) subsequence of A such that its length is between I and J and its sum is between X and Y. We present an online and an offline algorithm for the problems, both run in O(n log n) time, which are optimal.

关键词： length constraint longest subsequence offline algorithm online algorithm shortest subsequence sum constraint

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Joint Long-Term Admission Control and Beamforming in Green Downlink Networks: offline and Online Approaches

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第8期69卷 8710-8724页

作者： Lin, Jingran Ma, Mengyuan Li, Qiang Yang, Jian Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Peoples R China Peng Cheng Lab Shenzhen 518052 Peoples R China Northern Inst Elect Equipment China Beijing 100191 Peoples R China

Admission control is an effective solution to managing a wireless network with a large user set. It dynamically rejects users in bad conditions, and thereby guarantees high quality-of-service (QoS) for the others. Unfortunately, a frequently-varying admissible user set requests remarkable power to continually re-establish the transmission link. In this work, we explore the stability of admissible user set, and propose a joint long-term admission control and beamforming problem for a network with one multi-antenna base station (BS) and multiple single-antenna users. We consider the downlink transmission in a time period comprised of multiple time slices. By jointly optimizing the admissible users and the BS transmit beamformers in different time slices, we aim to balance the size of user set and the network total power cost for both QoS guarantee and user status switching. We develop two (offline and online) algorithms to find some efficient suboptimal solutions of this NP-hard problem. The offline algorithm requires all channel state information (CSI), and then solves the admissible users and beamformers in different time slices in one shot, based on successive upper-bound minimization (SUM). To support real-time data transmission, we further design an alternating direction method of multipliers (ADMM)-based online algorithm, which outputs the admissible users and beamformers in different time slices successively, utilizing the previous admissible user set, the actual value of current CSI, and the distribution of future CSI. Simulations validate the performance of the two algorithms, and show that the online algorithm is an efficient practical alternative to the offline algorithm.

关键词： Admission control Array signal processing Switches Channel estimation Handover Long-term admission control beamformer power minimization offline algorithm online algorithm

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PC-OPT: Optimal offline prefetching and caching for parallel I/O systems

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IEEE TRANSACTIONS ON COMPUTERS 2002年第11期51卷 1333-1344页

作者： Kallahalla, M Varman, PJ Hewlett Packard Labs Palo Alto CA 94304 USA Rice Univ Dept Elect & Comp Engn Houston TX 77251 USA

We address the problem of prefetching and caching in a parallel I/O system and present a new algorithm for parallel disk scheduling. Traditional buffer management algorithms that minimize the number of block misses are substantially suboptimal in a parallel I/O system where multiple I/Os can proceed simultaneously. We show that in the offline case, where a priori knowledge of all the requests is available, PC-OPT performs the minimum number of I/Os to service the given I/O requests. This is the first parallel I/O scheduling algorithm that is provably off line optimal in the parallel disk model. In the online case, we study the context of global L-block lookahead, which gives the buffer management algorithm a lookahead consisting of L distinct requests. We show that the competitive ratio of PC-OPT, with global L-block lookahead, is Theta(M - L + D), when L less than or equal to M, and Theta(MD/L), when L > M, where the number of disks is D and buffer size is M.

关键词： parallel I/O systems caching prefetching scheduling buffer management competitive ratio algorithms online algorithm offline algorithm

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Optimal offline and Competitive Online Strategies for Transmitter-Receiver Energy Harvesting

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IEEE TRANSACTIONS ON INFORMATION THEORY 2016年第8期62卷 4674-4695页

作者： Satpathi, Siddhartha Nagda, Rushil Vaze, Rahul Univ Illinois Dept Elect & Commun Engn Urbana IL 61801 USA IIT Roorkee Dept Appl Math Roorkee 247667 Uttar Pradesh India Tata Inst Fundamental Res Sch Technol & Comp Sci Bombay 400005 Maharashtra India

A joint transmitter-receiver energy harvesting model is considered, where both the transmitter and the receiver are powered by random (renewable) energy source. Given a fixed number of bits, the problem is to find the optimal transmission power profile at the transmitter and ON-OFF profile at the receiver to minimize the transmission time. With infinite capacity at both the transmitter and the receiver, the optimal offline and optimal online policies are derived. The optimal online policy is shown to be two-competitive in the arbitrary input case. With finite battery capacities at both ends, only random energy arrival sequence with given distribution is considered, for which an online policy with bounded expected competitive ratio is proposed.

关键词： Energy harvesting offline algorithm online algorithm competitive ratio

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offline Robust Model Predictive Control for Nonlinear Uncertain Systems

Offline Robust Model Predictive Control for Nonlinear Uncert...

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Chinese Automation Congress (CAC)

作者： Yang, Shizhong Xing, Lijuan Qingdao Technol Univ Coll Automat Engn Qingdao Peoples R China

ISBN: (纸本)9781538635247

In order to reduce the online calculation amount and improve the response speed, this paper proposes a robust model predictive control algorithm for nonlinear uncertain systems based on linear matrix inequality (LMI). The algorithm is divided into two parts: offline algorithm and online algorithm. In the offline algorithm, a sequence of asymptotically stable invariant ellipsoids and the corresponding control laws are got by one dimensional state variables optimization. The paper gives the calculating formula for one dimensional state variables parameter values, and explains the control laws got by the offline algorithm call guarantee the rapidity and stability of the system control. Due to the offline algorithm has completed most of the computation, when online, It only need to find suitable control laws in the parameter table according to the position of the system state variables in the ellipsoids, so it reduces the online algorithm complexity and the calculation cost. Through the simulation control effect comparing between the new algorithm and the traditional online control algorithm, the simulated results demonstrate the effectiveness of the new algorithm.

关键词： robust model predictive control LML nonlinear uncertain systems offline algorithm ellipsoid

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Optimal offline and Competitive Online Strategies for Transmitter-Receiver Energy Harvesting

Optimal Offline and Competitive Online Strategies for Transm...

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IEEE International Conference on Communications (ICC)

作者： Nagda, Rushil Satpathi, Siddhartha Vaze, Rahul IIT-Roorkee India IIT Kharagpur India TIFR Mumbai India

ISBN: (纸本)9781467364324

Transmitter-receiver energy harvesting model is assumed, where both the transmitter and receiver are powered by random energy source. Given a fixed number of bits, the problem is to find the optimal transmission power profile at the transmitter and ON-OFF profile at the receiver to minimize the transmission time. Structure of the optimal offline strategy is derived together with an optimal offline policy. An online policy with competitive ratio of strictly less than two is also derived.

关键词： Energy harvesting offline algorithm online algorithm competitive ratio

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Cost Minimization algorithms for Data Center Management

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2017年第1期28卷 60-71页

作者： Shi, Lei Shi, Yi Wei, Xing Ding, Xu Wei, Zhenchun Hefei Univ Technol Dept Comp & Informat Hefei Anhui Peoples R China Intelligent Automat Inc Rockville MD USA Hefei Univ Technol Inst Ind & Equipment Technol Hefei Anhui Peoples R China

Due to the increasing usage of cloud computing applications, it is important to minimize energy cost consumed by a data center, and simultaneously, to improve quality of service via data center management. One promising approach is to switch some servers in a data center to the idle mode for saving energy while to keep a suitable number of servers in the active mode for providing timely service. In this paper, we design both online and offline algorithms for this problem. For the offline algorithm, we formulate data center management as a cost minimization problem by considering energy cost, delay cost (to measure service quality), and switching cost (to change servers's active/idle mode). Then, we analyze certain properties of an optimal solution which lead to a dynamic programming based algorithm. Moreover, by revising the solution procedure, we successfully eliminate the recursive procedure and achieve an optimal offline algorithm with a polynomial complexity. For the online algorithm, We design it by considering the worst case scenario for future workload. In simulation, we show this online algorithm can always provide near-optimal solutions.

关键词： Data center management offline algorithm dynamic programming online algorithm

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