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Natural language provides a flexible, intuitive way for people to command robots, which is becoming increasingly important as robots transition to working alongside people in our homes and workplaces.
Journal ArticleDOI
01 Mar 2005-Interactions
65 Citations
After all, personal robots should not only be useful to their human users, but ideally people will genuinely enjoy having their robots around.
Open accessProceedings ArticleDOI
09 Mar 2009
298 Citations
The experimental results suggest promising potential for robots working in shopping malls.
This robot will be a platform for developing various types of service robots, such as cleaning robots, security patrol robots, and entertainment robots, based on a rich communication ability.
Enabling robots to understand instructions provided via spoken natural language would facilitate interaction between robots and people in a variety of settings in homes and workplaces.
The results show that the PLANET approach to mobile Web search robots significantly reduces the amount of data transferred via the Internet and that it enables the robots to work more efficiently than the robots in the conventional stationary scheme whenever nontrivial amounts of HTML files are processed.

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What are the current advancements in motion control technologies for autonomous mobile robots?
4 answers
Current advancements in motion control technologies for autonomous mobile robots include a range of approaches. These advancements encompass methods such as signal-based and model-based estimation, terramechanics-based techniques, machine learning, and global sensing methods. Motion control is crucial for trajectory adjustment and intelligent navigation, achieved through trajectory optimization using physics models. Innovations like deep learning for marker recognition and marker placement strategies have improved the accuracy and distance limitations of autonomous path travel control systems. Additionally, integrated chassis control frameworks with velocity-tracking controllers, nonlinear model predictive control, and active fault-tolerant control algorithms enhance driving stability, braking safety, and energy recapture in autonomous mobile robots. These advancements collectively aim to enhance the performance, safety, and autonomy of mobile robots in various applications.
How to use LLM?
5 answers
To utilize Large Language Models (LLMs) effectively, researchers can leverage their capabilities in various ways. Firstly, LLMs like GPT-4 can be employed to generate scripts for robot operations in biological experiments based on ambiguous instructions, simplifying the automation process. Understanding the nuances of LLMs from the perspectives of models, data, and downstream tasks is crucial for practitioners working with these models in natural language processing tasks. Additionally, exploring LLMs' potential in replicating human-like behavior in crowdsourcing tasks can provide insights into their abilities and limitations, especially in complex tasks that involve multiple sub-tasks. By considering these aspects and utilizing LLMs appropriately, researchers and practitioners can harness the power of these models for a wide range of applications in various fields.
What are the limitation to operationalize human-centered, trustworthy and ethical ai?
4 answers
The operationalization of human-centered, trustworthy, and ethical AI faces several limitations. One key challenge is the abstract nature and diversity of ethical principles, making them difficult to implement effectively. Additionally, the lack of practical guidance on how to apply these principles in real-world AI systems hinders their operationalization, leading to gaps between principles and execution. Furthermore, the need for a systematic overview of relevant values and an indicator system to assess design features complicates the implementation of ethical AI practices. The complexity of ensuring AI systems are safe, secure, healthy, trusted, and compliant with laws and ethical expectations adds another layer of difficulty in operationalizing human-centered and trustworthy AI. These challenges highlight the multifaceted nature of implementing ethical AI principles in practice.
Why is the range of motion and important parameter in the context of hemiparesis rehabiliation post-stroke?
5 answers
Range of motion (ROM) is a crucial parameter in hemiparesis rehabilitation post-stroke due to its impact on muscle strength, gait adaptability, and overall functional recovery. Restricted hip ROM, common in stroke patients, hinders walking performance and speed. ROM exercises can enhance muscle strength, leading to improved physical mobility and independence in activities of daily living. Determining the minimal clinically important differences (MCID) in hip ROM post-stroke aids in assessing intervention effects and designing effective rehabilitation programs. Additionally, gait adaptability training focusing on ROM normalization can significantly benefit patients by improving gait parameters and maintaining positive outcomes over time. Therefore, monitoring and improving ROM play a vital role in optimizing hemiparesis rehabilitation outcomes post-stroke.
How does brand anthropomorphism impact different customer segment?
5 answers
Brand anthropomorphism can significantly influence customer reactions based on various factors. Research suggests that consumers may perceive brands as possessing human-like qualities. The culture of a brand's origin plays a crucial role in shaping the brand's personality, with traits being transmitted differently to brand personalities (BPs). Additionally, the fit between a brand's personality and the type of service robot implemented can impact customer reactions, especially when the brand has a sincere personality. This interaction between brand personality and service robot type highlights the importance of aligning brand characteristics with technological implementations to mitigate negative customer responses. Therefore, understanding brand anthropomorphism and its alignment with customer expectations is essential for effective brand management and customer engagement.
Can can facilitate studying small-scale environmental processes in highly heterogeneous environments.?
5 answers
Studying small-scale environmental processes in highly heterogeneous environments can be facilitated by considering factors such as resource availability, spatial gradients, and the impact of environmental conditions on infection risk. For instance, research on plant diversity in grasslands highlights the positive effects of small-scale heterogeneity under low-resource conditions. Similarly, investigations on infection risk in snails by trematode parasites emphasize the importance of controlled field experiments to understand small-scale variation in infection risk driven by environmental gradients. Furthermore, the assessment of heterogeneous media in industrial processes showcases the significance of understanding processes that alter material properties at small scales. By integrating insights from these studies, researchers can gain a comprehensive understanding of how small-scale environmental processes are influenced by heterogeneity, aiding in effective study design and management strategies.
What are the challenges and opportunities for cobot deployment in industry-specific contexts?
5 answers
Challenges and opportunities for cobot deployment in industry-specific contexts are multifaceted. Challenges include the need for reliable dynamic modeling to ensure safe human-robot interaction, determining optimal task allocation between humans and cobots, and the requirement for frequent reprogramming to adapt to dynamic processes in low-volume manufacturing. On the other hand, opportunities lie in the potential for close collaboration between humans and cobots, leading to increased productivity and flexibility in manufacturing operations. Additionally, the adoption of cobots and AI-enabled devices in healthcare sectors presents opportunities for improving patient outcomes and enhancing the efficiency of healthcare practitioners' work. Understanding these challenges and opportunities is crucial for successful cobot integration in various industry-specific settings.
How widely automation is adopted in manufacturing companies?
4 answers
Automation technologies, including robotic systems, artificial intelligence, and process automation, are increasingly adopted in manufacturing companies worldwide. Research shows that these technologies are crucial for enhancing productivity, reducing costs, and improving efficiency. The adoption of automation technologies remains low in some sectors, but large and younger firms are more likely to embrace them. These technologies are utilized to automate tasks previously done by labor, leading to higher productivity and changes in skill requirements within the workforce. In China, automation technologies like intelligent technology and flexible automation are extensively used to enhance the competitiveness of the mechanical manufacturing industry. Overall, automation is becoming a cornerstone in modern manufacturing, offering numerous benefits to companies that implement these technologies.
Domestic using IA review paper
5 answers
The review paper on internal auditing (IA) post-Enron analyzed 471 papers from 64 journals between 2005 and 2018, highlighting a lack of significant contributions to understanding the internal audit function (IAF). The literature predominantly focuses on the American context, particularly publicly listed companies, and lacks references to theory, with a reliance on positivist analyses. The review suggests that future IA research should address emerging challenges by exploring factors that enhance the effectiveness and measurability of IA practices, considering regions like emerging economies and organizational settings such as private SMEs and not-for-profit organizations. This comprehensive analysis provides valuable insights for researchers seeking appropriate outlets and emerging scholars defining their research directions.
How to quantify the performance of multi-robot system?
5 answers
To quantify the performance of a multi-robot system, various methods can be employed. One approach involves modeling the system architecture using an Architecture Description Language (ADL) like BPMN, simulating the behaviors and interactions of the components using software agents like JADE, and analyzing the system's performance through quantitative measurements. Additionally, considering communication constraints within the system, such as intermittent connectivity and communication range restrictions, is crucial for accurate performance evaluation. Furthermore, utilizing multiple robots collaboratively can enhance performance, with factors like team size, initial positions, planning budget, and inter-robot communication impacting quantile estimation accuracy. Moreover, analyzing the kinematic behavior of mobile robots and reconstructing chaotic attractors in phase space can provide insights into robot interaction mechanisms and performance evaluation based on eigenvalues.
Metric for comparing different swarm robotic system?
5 answers
A metric for comparing different swarm robotic systems can be crucial in determining their scalability, flexibility, emergence, and robustness. Various quantitative measures have been proposed to assess the performance of swarm control algorithms, enabling systematic analysis and comparison to make informed design decisions. These metrics help in evaluating the ability of algorithms to handle different problem sizes and operating conditions, ensuring efficient system design and performance evaluation. Additionally, the introduction of error metrics that provide quantitative measures of coverage can further enhance the evaluation process, offering continuous sensitivity to changes in swarm distribution and aiding in choosing swarm size and robot configurations for optimal performance.