Authors: Ronit Chopra
Certificate: View Certificate
This article offers an overview of the dynamic intersection of artificial intelligence, robotics, and their impact on economic and organizational dynamics. We delve into the burgeoning research streams that explore the multifaceted consequences of these cutting-edge technologies in the fields of economics and management. Drawing from the diverse approaches adopted by scholars in this field, we provide insights into the implications of artificial intelligence, robotics, and automation for organizational design and firm strategy. We call for increased attention and involvement by organizational and strategy researchers in these areas and outline promising avenues for future research endeavors.
Artificial intelligence (AI) and robotics have emerged as revolutionary technologies with the potential to transform various aspects of society and the economy. By integrating AI into robotics, machines can now autonomously perceive, reason, and act in complex environments, leading to the development of advanced robotic systems in industries such as manufacturing, healthcare, and logistics. Moreover, the intersection of AI and robotics has opened up new possibilities in fields such as human-robot interaction, social robotics, and cognitive robotics. As a result, there has been a growing body of research investigating the latest advancements, challenges, and potential applications of AI in robotics. In this review paper, our goal is to provide an overview of the current state of AI in robotics, highlighting research trends, technical approaches, and real-world use cases, while also addressing ethical, social, and economic implications of this rapidly evolving field. Through this review, we aim to contribute to the understanding of the current landscape and future prospects of AI in robotics, shedding light on the opportunities and challenges associated with this cutting-edge technology.
II. LITERATURE REVIEW
Artificial intelligence (AI) has emerged as a significant technological advancement with the potential to revolutionize the field of robotics. In recent years, there has been a growing interest in integrating AI techniques into robotic systems, enabling them to perform tasks autonomously and adapt to changing environments. Machine learning techniques, including supervised, unsupervised, and reinforcement learning, have been extensively employed in robotics to enable robots to learn from data and make decisions based on patterns and experiences. Computer vision, a subfield of AI, has also played a crucial role in enhancing robotic perception capabilities, allowing robots to perceive and understand their surroundings through visual information. Furthermore, natural language processing (NLP) has been utilized to facilitate human-robot interaction, enabling robots to understand and generate human language for communication and collaboration. NLP techniques have been applied in various robotic applications, such as personal assistance robots, service robots, and social robots, to improve their ability to interact with humans in a more intuitive and natural manner. Deep learning, which involves training artificial neural networks with large amounts of data, has demonstrated remarkable performance in many robotics tasks, including object recognition, speech recognition, and motion planning. Reinforcement learning, a type of machine learning, has also been used to train robots to learn optimal decision-making policies through trial-and-error interactions with their environments. Apart from technical advancements, ethical considerations surrounding the use of AI in robotics have gained significant attention. Ethical issues, such as safety, transparency, accountability, and bias in decision-making, need to be addressed to ensure responsible and ethical deployment of AI-powered robots in various domains. Despite the rapid progress in AI for robotics, challenges remain, including the limitations of AI algorithms in handling uncertain and dynamic environments, as well as issues related to safety, robustness, and interpretability. Moreover, the social and economic impacts of widespread adoption of AI in robotics, including the potential impact on employment and societal norms, need to be carefully considered. Nevertheless, the potential applications of AI in robotics are vast and diverse, with the integration of AI and robotics expected to continue advancing and shaping the future of automation, creating new opportunities and challenges for researchers, engineers, policymakers, and society as a whole.
A. Health Care
The integration of artificial intelligence (AI), machine learning (ML), and robotics in agriculture provides agronomists with valuable insights to enhance farm productivity. By leveraging this information, farmers can achieve high yields and low operational costs, ultimately leading to farm success. The adoption of robotics in farming aims to automate labor-intensive tasks such as irrigation, seed distribution, pest control, and harvesting, freeing up farmers' time to focus on more productive activities. One of the key advantages of robotics in agriculture is precision, which helps optimize land utilization and reduce wastage. This technology also enables monitoring of quality enhancement and environmental conservation in the green economy. As the agricultural community gradually shifts towards AI and robotics, it promises significant success in the broader context of sustainable development, aligning with the goals of the United Nations and the global focus on sustainability. The integration of AI and robotics in agriculture has the potential to drive positive change and contribute to the overall improvement of the global agricultural landscape.
Large companies with expansive storages are avaricious druggies of robotics due to their capability to reduce functional time and intermediate costs. These storages use high- tech detectors, including visual, audile, thermal, and haptic detectors, to enable independent operation of robots. The integration of AI has further enhanced safety through better perception of the girding terrain, particularly with thermal and haptic detectors. These detectors serve as the decision- making medium for robots, allowing them to operate effectively. Automated guided vehicles( AGVs) or automated guided wagons( AGCs) are generally employed for stock transportation within storages, enabling round- the- timepiece operations with harmonious costs. Upstanding drones are also being decreasingly used in storages for quick force scanning and optimization with minimum trouble. espousing robotics in storages offers several benefits, similar as minimum crimes, rigidity, and safety. Robots, designed with mortal- suchlike numbers and trained algorithms, can operate without making miscalculations. Safety is a significant advantage of robotics, as it eliminates the need for workers to perform parlous tasks, similar as pulling stocks from heights, thereby reducing the eventuality for accidents. In summary, robotics in storages give multitudinous advantages, including bettered effectiveness, rigidity, and safety, relieving workers from mundane and dangerous tasks.
D. Motor Cars
Robotics plays a vital part in the automotive assiduity, encompassing a wide range of operations from design and force chain operation to product conditioning and overall operations. Transportation for the machine assiduity benefits from systems similar as motorist backing, independent driving, and motorist threat backing. The integration of robotic intelligence in the automotive assiduity has been current for over 50 times, with significant advancements in AI and ML in recent times. The advantages of robotics in motorcars are multifarious, including. Accurate vision for locating and situating needed particulars, easing tasks similar as installing door panels, buffers, and other factors.
Assembly of machine bias similar as motors, screws, pumps, etc. with perfection and effectiveness. Deployment of robotic arms in oil and coating processes, icing harmonious quality and uniformity. Ability to transfer and handle segregated corridor, including lading and unloading, streamlining product processes and reducing homemade labour. In summary, robotics in the automotive assiduity offer multitudinous benefits, ranging from accurate vision for locating and situating factors to effective assembly and running of machine bias, contributing to bettered productivity and quality in the overall manufacturing process.
IV. ALGORITHMS USED FOR ROBOTICS
V. ETHICAL CHALLENGES AND COUNTERMEASURES OF DEVELOPING ADVANCED ARTIFICIAL INTELLIGENCE AND ROBOTS
4. The challenge of automating moral opinions, similar as the trade- off between guarding passengers in an independent vehicle versus girding climbers, is a significant concern. masterminds must strive to develop systems that don't pose pitfalls of severe adverse events and gain nonsupervisory blessing to insure social adequacy. still, this can be complex and requires careful consideration of implicit changeable actions that may arise in real- world scripts. similar ethical challenges have braked the relinquishment of independent vehicles.
5. To address these ethical challenges, countermeasures can be taken, including incorporating machine ethics and enforcing developer preventives. This involves designing AI and robotic systems with erected- in mechanisms to automatically limit geste inform drivers of conditions that bear mortal review, and consider different ethical perspectives. Overall, a visionary approach towards addressing ethical challenges associated with AI and robotics is pivotal to insure responsible and socially respectable deployment of these technologies in our society.
VI. DISTRIBUTIONAL GOODS OF ARTIFICIAL INTELLIGENCE AND ROBOTICS
Artificial Intelligence (AI) and robotics have the potential to transform society, but they also present ethical challenges. These include concerns about misuse, autonomy, biases, transparency, and impact on employment and human interaction. To address these challenges, ethical considerations should be integrated into the design process, including identifying and mitigating biases, ensuring transparency and human oversight, and promoting machine ethics aligned with human values. Education and awareness programs, along with regulations and policies, should be established to govern the ethical use of AI and robots, with close collaboration between policymakers, technologists, and ethicists. By prioritizing ethical decision-making and responsible practices, we can harness the benefits of AI and robotics for the betterment of society. In conclusion, various algorithms employed in AI for robotics come with their own strengths and limitations. Reinforcement learning excels in adaptive decision-making, supervised learning is beneficial for labelled data tasks, computer vision provides visual perception capabilities, SLAM is critical for navigation and mapping, evolutionary algorithms are effective in optimization, and deep learning is powerful for perception and control. The selection of the appropriate algorithm depends on the task requirements, data availability, computational resources, and desired autonomy level for the robot.
 https://link.springer.com/article/10.1186/s41469-019-0050-0  https://www.frontiersin.org/articles/10.3389/frobt.2017.00075/full  https://emeritus.org/in/learn/role-of-artificial-intelligence-and-machine-learning-in-robotics/#:~:text=Artificial%20intelligence%20teaches%20functions%20like,on%20unseen%20data%20and%20situations.  https://www.accenture.com/us-en/insights/future-workforce/transforming-learning  https://ieeexplore.ieee.org/abstract/document/1423975  http://ai-elsi.org/wp-content/uploads/2017/05/JSAI-Ethical-Guidelines-1.pdf  https://aichatgpt.co.za/artificial-intelligence-in-robotics-research-paper/#Current_State_of_Robotics_and_AI  https://arxiv.org/pdf/1707.07217.pdf  https://www.sciencedirect.com/science/article/pii/S0004370217300310  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803010
Copyright © 2023 Ronit Chopra. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.