What are the limitations of current robot collaboration technology in the hospitality industry?

Technology evolves rapidly and have been part of various functions now and so does hospitality. However i feel there are some limitations which will definitely evolve as technology updates at faster pace: 1.adaptability and flexibility- robots may struggle to respond in change in environment or some of the crucial unexpected situations. 2.high cost- initial cost is fine however maintenance can be much higher as customer expectations are changing rapidly 3.social accpetance- may face few challenges in accepting robots as hospitality staff in some cases by customers 4. cognitive ability-though basic or advance AI is available in robots but sometimes understanding personal customized requirements of customer might be difficult for robots.

Automation is being used in the hospitality industry to handle complex duties, but there are technological and economical concerns. We need dexterity, adaptability, situational awareness, and high ROI. Safety, job displacement, and lack of human interaction affect customers and employees. Integration and training are challenging, thus robots are best for daily tasks. Robots need sensors and safety features to avoid harm. Guest and employee safety requires regular maintenance and downtime. Regulatory compliance is necessary since robots can grab and store guest data. Without industry norms, robots may not converse. Researchers, developers, and industry stakeholders should improve robot dexterity, develop cost-effective solutions.

Robots in hospitality are typically not well-equipped for natural human interaction. While some robots have speech recognition and limited conversational capabilities, they often lack the emotional intelligence and understanding necessary to engage guests in meaningful conversations or handle complex customer service issues.

So we divide this with 2 different kind of robots. One fixed floor mounted and another mobile robots. Yes there are many limitations in fixed floor mounted robot and its due to emotional intelligence that robots can not learn without AI and that too when AI is in developing stage. But yes, autonomous-mobile robots are not new for medical industry .

In my experience, I have seen that creating a seamless collaborative environment for robots is quite complex. Issues around communication protocols, software compatibilities, designing appropriate control algorithms are just few of the challenges. Others include fusing emotions and human contexts into the algorithms. In a collaborative environment, robots must learn to be adaptive and achieving this is tough but can be done. So in the hospitality industry, all these components must come together. Privacy of information is still a big concern so a lot of companies are investing in IDS to mitigate this.

The lack of AI and machine learning and lag in response to the environment is so obvious in today's haptic industry. Engineers must think outside of the box and let the main process happen in GPU. OpenGL underestimated. TensorFlow and OpenCV are all underrated. 90% of hardware haptic programmers don't know how to use more than 30%~50% of Atmega, Arm, Cortex, Snapdragon, Ryzer, and Tegra. Less than 10% of hardware programmers in haptic confidently use FPGA, AM & TM Texas Instruments chips. The haptic industry needs a major change in my point of view.

Current robot collaboration technology in the hospitality industry often struggles with developing advanced social skills. Robots may have limitations in understanding and responding appropriately to subtle human cues, emotions, or complex social scenarios. Enhancing these social skills is crucial for improving guest interactions and ensuring robots can seamlessly integrate into social environments within the hospitality sector.

We are still struggling with the ethics of caregiving and the behavior of human doctors in regards to health services; Robots and AI will have the challenge of treating different patients in accordance to their specific needs. We need to ensure robots will behave in an acceptable manner in unpredictable and hectic environments, such as the ones found in many hospitals.

Robot is then a real robot, when it can adopt to the schamfilt environment according to the task it is created for. Computer vision one of is the input channels of a robot. The output is operating with the robotic manipulator in real time. For healthcare the most obvious solution is to use colloborative arm. Kuka LBR med as an example. The challenge is that not every cobot is suitable to be operated in real time. They all have different operational logic, interfaces, control boxes of various stability. And as the industry of cobots is still young, sometimes you cannot have a stable and predictable solution as it is mentioned in tech specs. Using ROS makes you more more flexible in terms of future changes.

Task allocation in current robot collaboration technology within the hospitality industry may face challenges in efficiently distributing and adapting to various tasks. Robots might struggle to dynamically allocate tasks based on real-time demands, leading to potential inefficiencies in service delivery. Improving the adaptability and intelligence of task allocation algorithms is essential for enhancing the overall performance and effectiveness of robots in hospitality settings.

The use of robots in the hospitality industry raises ethical and privacy concerns, particularly with regard to data security and guest privacy. The collection and storage of guest information and interactions with robots can lead to privacy-related issues if not managed properly.

Robots in the hospitality industry pose ethical and legal issues, including human interaction, data protection, bias, and discrimination. Robotic systems may collect and store sensitive guest data, raising concerns about privacy and data protection. Businesses must implement robust measures to safeguard guest information and ensure transparency in data collection practices. Additionally, businesses must comply with relevant laws governing data privacy, labor practices, accessibility, and safety. Legal considerations include regulatory compliance, liability, intellectual property rights, cybersecurity, and accessibility for guests with disabilities.

In the realm of robot collaboration in the hospitality industry, ethical concerns include issues related to privacy, data security, and the potential impact on employment. There may be questions about how robots handle sensitive guest information and the ethical implications of their interactions. Legal considerations involve compliance with data protection laws, liability for errors or accidents, and navigating regulations surrounding the use of automation in service industries. Addressing these ethical and legal challenges is crucial for responsible and lawful deployment of robot technology in hospitality.

reliability is the most important issue of automation in any field, especially collaborative robots. These days we have reached enough maturity in technology but strategy-making and reliability are even raw.

Other factors to consider in current robot collaboration technology for the hospitality industry include: 1. Costs: Implementation costs, maintenance expenses, and the overall financial viability of integrating robots into hospitality operations. 2. User Acceptance: Understanding and addressing potential resistance or concerns from guests and staff regarding the use of robots in service roles. 3. Maintenance and Reliability: Ensuring that robots are robust, reliable, and easy to maintain to minimize downtime and disruptions in service. 4. Customization: 5. Integration with Existing Systems: 6. Training Requirements: 7. Sustainability: 8. Cultural Sensitivity:

Complexity in Unpredictable Environments: Robots typically perform well in controlled environments but may struggle in unpredictable or highly variable settings, which are common in hospitality.

The big challenge for robots in hospitability is the voice interface, today, only ChatGPT voice has an acceptable level. Other voice assistants as Siri or Alexa, are not yet ready for a good user experience.