Autonomous Robots最新文献_第6页

Learning modular language-conditioned robot policies through attention 通过注意力学习模块化语言条件机器人策略

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-08-30 DOI: 10.1007/s10514-023-10129-1

Yifan Zhou, Shubham Sonawani, Mariano Phielipp, Heni Ben Amor, Simon Stepputtis

引用次数: 1

Integrating action knowledge and LLMs for task planning and situation handling in open worlds 整合行动知识和法学硕士在开放世界的任务规划和情况处理

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-08-29 DOI: 10.1007/s10514-023-10133-5

Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Andy Kaminski, Chad Esselink, Shiqi Zhang

{"title":"Integrating action knowledge and LLMs for task planning and situation handling in open worlds","authors":"Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Andy Kaminski, Chad Esselink, Shiqi Zhang","doi":"10.1007/s10514-023-10133-5","DOIUrl":"10.1007/s10514-023-10133-5","url":null,"abstract":"<div><p>Task planning systems have been developed to help robots use human knowledge (about actions) to complete long-horizon tasks. Most of them have been developed for “closed worlds” while assuming the robot is provided with complete world knowledge. However, the real world is generally open, and the robots frequently encounter unforeseen situations that can potentially break theplanner’s completeness. Could we leverage the recent advances on pre-trained Large Language Models (LLMs) to enable classical planning systems to deal with novel situations? This paper introduces a novel framework, called COWP, for open-world task planning and situation handling. COWP dynamically augments the robot’s action knowledge, including the preconditions and effects of actions, with task-oriented commonsense knowledge. COWP embraces the openness from LLMs, and is grounded to specific domains via action knowledge. For systematic evaluations, we collected a dataset that includes 1085 execution-time situations. Each situation corresponds to a state instance wherein a robot is potentially unable to complete a task using a solution that normally works. Experimental results show that our approach outperforms competitive baselines from the literature in the success rate of service tasks. Additionally, we have demonstrated COWP using a mobile manipulator. Supplementary materials are available at: https://cowplanning.github.io/</p></div>","PeriodicalId":55409,"journal":{"name":"Autonomous Robots","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136248667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

ProgPrompt: program generation for situated robot task planning using large language models ProgPrompt:使用大型语言模型生成定位机器人任务规划的程序

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-08-28 DOI: 10.1007/s10514-023-10135-3

Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg

{"title":"ProgPrompt: program generation for situated robot task planning using large language models","authors":"Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg","doi":"10.1007/s10514-023-10135-3","DOIUrl":"10.1007/s10514-023-10135-3","url":null,"abstract":"<div><p>Task planning can require defining myriad domain knowledge about the world in which a robot needs to act. To ameliorate that effort, large language models (LLMs) can be used to score potential next actions during task planning, and even generate action sequences directly, given an instruction in natural language with no additional domain information. However, such methods either require enumerating all possible next steps for scoring, or generate free-form text that may contain actions not possible on a given robot in its current context. We present a programmatic LLM prompt structure that enables plan generation functional across situated environments, robot capabilities, and tasks. Our key insight is to prompt the LLM with program-like specifications of the available actions and objects in an environment, as well as with example <span>programs</span> that can be executed. We make concrete recommendations about prompt structure and generation constraints through ablation experiments, demonstrate state of the art success rates in VirtualHome household tasks, and deploy our method on a physical robot arm for tabletop tasks. Website and code at progprompt.github.io</p></div>","PeriodicalId":55409,"journal":{"name":"Autonomous Robots","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10514-023-10135-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48320797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Learning scalable and efficient communication policies for multi-robot collision avoidance 学习可扩展且高效的多机器人防撞通信策略

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-08-19 DOI: 10.1007/s10514-023-10127-3

Álvaro Serra-Gómez, Hai Zhu, Bruno Brito, Wendelin Böhmer, Javier Alonso-Mora

{"title":"Learning scalable and efficient communication policies for multi-robot collision avoidance","authors":"Álvaro Serra-Gómez, Hai Zhu, Bruno Brito, Wendelin Böhmer, Javier Alonso-Mora","doi":"10.1007/s10514-023-10127-3","DOIUrl":"10.1007/s10514-023-10127-3","url":null,"abstract":"<div><p>Decentralized multi-robot systems typically perform coordinated motion planning by constantly broadcasting their intentions to avoid collisions. However, the risk of collision between robots varies as they move and communication may not always be needed. This paper presents an efficient communication method that addresses the problem of “when” and “with whom” to communicate in multi-robot collision avoidance scenarios. In this approach, each robot learns to reason about other robots’ states and considers the risk of future collisions before asking for the trajectory plans of other robots. We introduce a new neural architecture for the learned communication policy which allows our method to be scalable. We evaluate and verify the proposed communication strategy in simulation with up to twelve quadrotors, and present results on the zero-shot generalization/robustness capabilities of the policy in different scenarios. We demonstrate that our policy (learned in a simulated environment) can be successfully transferred to real robots.\u0000</p></div>","PeriodicalId":55409,"journal":{"name":"Autonomous Robots","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10514-023-10127-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46045076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Humans as path-finders for mobile robots using teach-by-showing navigation 人类作为移动机器人的寻路者，使用指示式导航

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-08-17 DOI: 10.1007/s10514-023-10125-5

Alessandro Antonucci, Paolo Bevilacqua, Stefano Leonardi, Luigi Paolopoli, Daniele Fontanelli

引用次数: 0

Pseudo-trilateral adversarial training for domain adaptive traversability prediction 伪三边对抗训练域自适应可穿越性预测

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-08-02 DOI: 10.1007/s10514-023-10123-7

Zheng Chen, Durgakant Pushp, Jason M. Gregory, Lantao Liu

{"title":"Pseudo-trilateral adversarial training for domain adaptive traversability prediction","authors":"Zheng Chen, Durgakant Pushp, Jason M. Gregory, Lantao Liu","doi":"10.1007/s10514-023-10123-7","DOIUrl":"10.1007/s10514-023-10123-7","url":null,"abstract":"<div><p>Traversability prediction is a fundamental perception capability for autonomous navigation. Deep neural networks (DNNs) have been widely used to predict traversability during the last decade. The performance of DNNs is significantly boosted by exploiting a large amount of data. However, the diversity of data in different domains imposes significant gaps in the prediction performance. In this work, we make efforts to reduce the gaps by proposing a novel pseudo-trilateral adversarial model that adopts a coarse-to-fine alignment (CALI) to perform <i>unsupervised domain adaptation</i> (UDA). Our aim is to transfer the perception model with high data efficiency, eliminate the prohibitively expensive data labeling, and improve the generalization capability during the adaptation from easy-to-access <i>source domains</i> to various challenging <i>target domains</i>. Existing UDA methods usually adopt a bilateral zero-sum game structure. We prove that our CALI model—a pseudo-trilateral game structure is advantageous over existing bilateral game structures. This proposed work bridges theoretical analyses and algorithm designs, leading to an efficient UDA model with easy and stable training. We further develop a variant of CALI—Informed CALI, which is inspired by the recent success of mixup data augmentation techniques and mixes informative regions based on the results of CALI. This mixture step provides an explicit bridging between the two domains and exposes under-performing classes more during training. We show the superiorities of our proposed models over multiple baselines in several challenging domain adaptation setups. To further validate the effectiveness of our proposed models, we then combine our perception model with a visual planner to build a navigation system and show the high reliability of our model in complex natural environments.</p></div>","PeriodicalId":55409,"journal":{"name":"Autonomous Robots","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135016477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Design and control of BRAVER: a bipedal robot actuated via proprioceptive electric motors 本体感觉电机驱动的两足机器人BRAVER的设计与控制

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-07-23 DOI: 10.1007/s10514-023-10117-5

Zhengguo Zhu, Weiliang Zhu, Guoteng Zhang, Teng Chen, Yibin Li, Xuewen Rong, Rui Song, Daoling Qin, Qiang Hua, Shugen Ma

引用次数: 1

An empirical characterization of ODE models of swarm behaviors in common foraging scenarios 常见觅食情景下群体行为的ODE模型的经验表征

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-07-23 DOI: 10.1007/s10514-023-10121-9

John Harwell, Angel Sylvester, Maria Gini

引用次数: 0

High-frame rate homography and visual odometry by tracking binary features from the focal plane 通过焦平面跟踪二进制特征实现高帧率单应性和视觉里程计

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-07-22 DOI: 10.1007/s10514-023-10122-8

Riku Murai, Sajad Saeedi, Paul H. J. Kelly

{"title":"High-frame rate homography and visual odometry by tracking binary features from the focal plane","authors":"Riku Murai, Sajad Saeedi, Paul H. J. Kelly","doi":"10.1007/s10514-023-10122-8","DOIUrl":"10.1007/s10514-023-10122-8","url":null,"abstract":"<div><p>Robotics faces a long-standing obstacle in which the speed of the vision system’s scene understanding is insufficient, impeding the robot’s ability to perform agile tasks. Consequently, robots must often rely on interpolation and extrapolation of the vision data to accomplish tasks in a timely and effective manner. One of the primary reasons for these delays is the analog-to-digital conversion that occurs on a per-pixel basis across the image sensor, along with the transfer of pixel-intensity information to the host device. This results in significant delays and power consumption in modern visual processing pipelines. The SCAMP-5—a general-purpose Focal-plane Sensor-processor array (FPSP)—used in this research performs computations in the analog domain prior to analog-to-digital conversion. By extracting features from the image on the focal plane, the amount of data that needs to be digitised and transferred is reduced. This allows for a high frame rate and low energy consumption for the SCAMP-5. The focus of our work is on localising the camera within the scene, which is crucial for scene understanding and for any downstream robotics tasks. We present a localisation system that utilise the FPSP in two parts. First, a 6-DoF odometry system is introduced, which efficiently estimates its position against a known marker at over 400 FPS. Second, our work is extended to implement BIT-VO—6-DoF visual odometry system which operates under an unknown natural environment at 300 FPS.\u0000</p></div>","PeriodicalId":55409,"journal":{"name":"Autonomous Robots","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10514-023-10122-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47385185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Robust bounded control scheme for quadrotor vehicles under high dynamic disturbances 高动态扰动下四旋翼飞行器的鲁棒有界控制方法

IF 3.5 3区计算机科学

Autonomous Robots Pub Date : 2023-07-21 DOI: 10.1007/s10514-023-10124-6

J. Betancourt, P. Castillo, P. García, V. Balaguer, R. Lozano

引用次数: 0