scispace - formally typeset
Search or ask a question

How to switch between frames in robot framework? 

Answers from top 7 papers

More filters
Papers (7)Insight
This is more flexible than simply applying such effects to whole frames, as new relationships between objects can be created.
It is argued in this paper, that the same framework can be extended to robot navigation, but with the realization of the dimensions appearing quite different in robotics world.
Proceedings ArticleDOI
Xun Guo, Yan Lu, Wen Gao, Qingming Huang 
23 May 2005
17 Citations
The proposed scheme implements the switch function at the predictive frames and improves the efficiency of the switched frames by limiting the mismatch between the references for the prediction and the reconstruction.
With this param eterization, we can fully search the robot trajectory space and find the switch times that will produce particular paths to a desired final configuration of the platform.
Proceedings ArticleDOI
S.V. Ragavan, V. Ganapathy 
08 Oct 2007
10 Citations
This Framework though generic in nature can be applied quite successfully to specific problems like robot navigation and sensor fusion as discussed here.
It is shown how a programming theory with dynamic frames supports both features, without the use of alias control or any other kind of restriction.
Open accessJournal ArticleDOI
Sanjay J. Patel, Steven S. Lumetta 
204 Citations
Coupled with the high coverage of frames achieved through the dynamic frame construction, the success of these optimizations demonstrates the significance of the rePLay Framework.

See what other people are reading

How does a robot carry an object to a humans position?
5 answers
A robot can carry an object to a human's position through various methods based on advanced technologies and interaction strategies. One approach involves implementing a robot-to-human object handover algorithm utilizing sensor modalities like joint torque sensors and RGB-D cameras for real-time feedback. This algorithm enables the robot to autonomously hand over objects to humans with high accuracy by detecting the human receiver's intentions and hand movements. Another method involves employing adaptive impedance control for human-robot co-transportation, where vision and force sensing are used to track the human hand position and interaction force during object transportation tasks. These techniques ensure safe and smooth interaction between humans and robots during object handovers, enhancing the overall efficiency and user experience in human-robot collaborations.
How to make first time vr users comfortable?
4 answers
To make first-time VR users comfortable, several strategies can be implemented based on the research findings. Implementing discomfort reduction filters in VR content can help reduce potential discomfort. Additionally, allowing users to explore the full 360° area by moving their heads instead of their whole bodies, and reducing the viewing area to 225° instead of 180° can enhance comfort during VR experiences. Moreover, optimizing motion planning to minimize VR sickness and maximize comfort, such as through the use of Pareto-optimal trajectories, can significantly improve the user experience. Furthermore, providing comfortable VR glasses with features like memory sponge layers, waterproof medical silica gel layers, and detachable soft cotton cloth layers can greatly enhance the overall comfort of VR users.
How does culture influence behavior,discus in details?
5 answers
Culture significantly influences behavior by shaping values, norms, and beliefs. Cultural factors impact consumer behavior through societal norms and values, guiding how products are used and consumed. Certain culture traits, like social coordination conventions, influence behavior adaptively, reflecting gene-culture coevolution. Moreover, culture plays a crucial role in determining risk behaviors, affecting physical and mental health outcomes. Cultural differences in expectations from robots also highlight the impact of cultural backgrounds on behavior, emphasizing the need for cultural adaptation in human-robot interactions. Overall, culture acts as a pervasive force that shapes behaviors through values, norms, and societal influences, impacting various aspects of individual and collective actions.
What are foundational models in robotics?
5 answers
Foundation models in robotics refer to general-purpose pre-trained models that enable the development of adaptable solutions for various machine learning tasks with smaller datasets than those required for training from scratch. These models, such as the Visual Navigation Transformer (ViNT)and language-grounded segmentation masks, are trained on diverse datasets with weak supervision, allowing for efficient adaptation to different downstream applications. They enhance generalization capabilities, facilitate task specification through various modalities like images, sketches, or language descriptions, and support sample-efficient learning for robot manipulation tasks. Foundation models like ViNT exhibit positive transfer across different robotic platforms and can be augmented with subgoal proposals for exploring new environments, making them effective tools for mobile robotics.
How to generate texxture?
5 answers
To generate texture, various methods and technologies can be employed based on different contexts. One approach involves utilizing deep neural networks, such as recurrent neural networks, for text generation. Another method involves employing a text generation method and device that identifies objects in an image and queries associated knowledge point information from a knowledge graph, enabling diverse and accurate text generation based on image content. Additionally, a computer-implemented method for generating new formulations involves analyzing input formulations using a topic model algorithm, clustering constituent topics, and selecting materials to generate a new formulation based on input queries. These approaches showcase the use of advanced technologies and algorithms to facilitate texture generation in various contexts.
How do technical issues and system failures impact the efficiency of smart technology in hospitality industries?
5 answers
Technical issues and system failures can significantly impact the efficiency of smart technology in the hospitality industry. Smart services play a crucial role in enhancing employees' performance by providing insights into processes and tasks, ultimately improving effectiveness and efficiency. However, the integration of Internet of Things (IoT) technologies in smart hotels raises concerns about security and privacy, especially due to regulations like the General Data Protection Regulation (GDPR). To mitigate these issues, it is essential for hotels to invest in comprehensive infrastructure improvements, hire trained employees, and stay updated on technological advancements, particularly in the field of artificial intelligence. By addressing technical challenges and ensuring robust security measures, smart technology can continue to revolutionize the hospitality industry.
What are the key steps involved in the natural language processing (NLP) workflow?
5 answers
The key steps in a natural language processing (NLP) workflow involve several crucial processes. Firstly, acquiring the natural language text for processing. Next, utilizing deep neural networks for processing the text and generating target results. Additionally, incorporating domain knowledge in regular expression form during the training of neural network models to enhance performance in NLP tasks. Furthermore, detecting missing intent objects or purposes in user input, retrieving historical corpus information, and performing natural language analysis to improve man-machine interaction efficiency. Lastly, establishing a unified open-source framework that supports the development of sophisticated NLP workflows by encoding heterogeneous results, offering a repository of processors, and enabling customization through external NLP libraries.
Is mart city project costly to implement in general?
4 answers
Implementing Smart City projects can be costly due to various factors such as infrastructure development, technology integration, and data collection. The expense of Smart City projects is highlighted in different contexts. For instance, the research by Guna and Ariana discusses the impact of additional labor and overtime on project costs, indicating potential cost increases. Additionally, Ragab and Sabir emphasize the importance of anomaly detection in Smart City Infrastructures, which involves the use of advanced technologies like Deep Learning models, indicating the investment required for such systems. Moreover, Figliozzi and Bertini point out the challenges related to data accessibility and integration in Smart City planning, which can contribute to the overall costs of implementing Smart City initiatives. These insights collectively suggest that Smart City projects can indeed be costly to implement.
How do CNC machines compare to traditional manufacturing methods in terms of accuracy and efficiency?
4 answers
Traditional CNC machines are known for their high accuracy but are limited by workpiece size and axes. On the other hand, CNC machine tools' reliability significantly impacts the manufacturing process, with traditional reliability evaluation methods often lacking accuracy due to neglecting mission and load profiles. To enhance CNC machining accuracy, a STEP-NC feature-oriented simulation method has been proposed, focusing on dividing the workpiece into machining features for real-time simulation with efficiency and accuracy. Moreover, modern CNC machine tools still rely on archaic input systems, hindering intuitive operation. A novel manual programming system using control levers with force sensors aims to eliminate programming needs and enable intuitive machine movement, enhancing efficiency and reducing errors. Overall, CNC machines offer high accuracy and efficiency when combined with innovative approaches and technologies.
How attention and selective filtering impact perception in park?
5 answers
Attention and selective filtering play crucial roles in shaping perception in various contexts. By utilizing perceptual attention, which enhances relevant information while filtering out irrelevant details, robots can efficiently manage computing resources for tasks like navigation and recognition. In cognitive aging, attention is viewed as a distributed resource, with perceptual attention originating in posterior sensory subsystems to filter out unattended input early in the processing cycle. Studies on attention sets reveal that attention can be category-based, focusing on relations or categories rather than individual features of objects, impacting the likelihood of noticing unexpected events. Additionally, selective attention filters like the Selective Attention Filter (SAF) can enhance relevant information and filter out irrelevant pixels in complex map images, improving classification results.
How do autonomous systems impact the efficiency and cost-effectiveness of cafe operations?
5 answers
Autonomous systems in cafes significantly enhance efficiency and cost-effectiveness. These systems, such as the Automatic Café Management System (ACMS) based on the Internet of Things (IoT), unmanned automation cafe booth systems, and low-cost automatic cafe management systems utilizing waiter robots, streamline operations by automating tasks like order processing, coffee brewing, and food serving. They reduce the need for human intervention, minimizing errors and increasing operational efficiency. Additionally, autonomous coffee machines like the Bitbarista not only automate coffee consumption processes but also provide provenance data, aiming to cut intermediaries in the coffee trade. By leveraging technologies like smart contracts and distributed ledgers, these systems optimize cafe workflows, enhance customer experiences, and ultimately drive down operational costs.