As robotics technology advances and becomes more integrated in the industrial and service sectors, human-robot collaboration (HRC) has seen a dramatic change in recent years. Robots may now work more securely and efficiently with humans because to developments in sensing, artificial intelligence, and machine learning. The emergence of mobile assistants, service robots, and collaboration robots (also known as cobots) is indicative of a paradigm shift in how businesses support human labor and design workflows.
Dr. Vivian Chu, co-founder and Chief Innovation Officer of Diligent Robotics, a U.S.-based robotics business that creates socially intelligent robots for hospitals, spoke to the Impact to offer her expert insight. With a Ph.D. in robotics from Georgia Tech, Chu has worked on robot cognition, machine learning, and human-robot interaction (HRI) for more than ten years. Moxi, a mobile robot assistant used in hospitals for supply transportation, is one of her projects.
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Robotic usage is expanding across several verticals. Cobots are becoming more and more popular in manufacturing because they can work side by side with humans to complete repetitive tasks like screw driving, quality inspection, and assembly. In logistics and warehousing, autonomous mobile robots (AMRs) deliver goods, manage inventory flow, and reduce human workload. Another significant area is healthcare, where robots are now used in hospitals to assist with logistical support, sample transfer, and supply distribution. Another market that is expanding quickly is service robotics. Robots can perform everything from cleaning and distribution to helping in hospitals, according to business reports. Due to applications in vital industries including healthcare, hospitality, and assisted living, the total economic effect of service robots is anticipated to be in the tens of billions of dollars worldwide.
Coordination and safety continue to be major issues in HRC To prevent harm, robots must recognize human presence, react to sudden movement, and control force. Robot design is guided by standards such as ISO 10218 and ISO/TS 15066, especially when it comes to force limiting, speed, and proximity behavior.
These are the main queries posed to Chu regarding cooperation between humans and robots. How humans and robots function in the real world is a primary concern regularly expressed to her.
“Historically, a lot of robots have operated in predictable, organized settings like factories. Hospitals, on the other hand, offer congested, dynamic, and unexpected environments,” she said.
According to her, Moxi was designed to learn from humans through visual, aural, and tactile inputs, allowing it to modify its behavior instantly. “Rather of replacing people, Diligent Robotics aims to increase human productivity by handling low-value, repetitive jobs, freeing up employees to concentrate on patient-centered care.”
Communicaiton is a puzzling to concern to those not in the industry. Moxi’s design is socially expressive, it can convey direction and meaning by nodding, turning its head, and using LED “eyes.” According to Chu, “the robot anticipates motion and avoids collisions by using human-aware navigation and predictive models.”
Moxi 2.0 was designed with significantly more processing power (ten times that of its predecessor) in a later design iteration. Chu claims that this update enables predictive world models: Moxi 2.0 can anticipate elevator movement, plan trajectories, and function more fluidly in shared hospital settings instead of just responding to its surroundings.
Over 1.2 million things have been delivered by Moxi across its deployments in U.S. hospitals, according to Chu. She underlined that mundane duties like delivering test samples, replenishing rooms, and carrying supplies make up a large portion of nurses’ job and take time away from providing direct patient care. Moxi frees up healthcare staff time for important procedures, patient requirements, and paperwork by handling these routine tasks. She clarified that these gains are quantifiable: hospitals report lower staff time spent on nonclinical tasks, which leads to better labor distribution and workflow efficiency. Robots also lessen the accumulation of little jobs that might otherwise accumulate because they work regularly throughout shifts, including overnight.
Human-robot cooperation in healthcare has an impact on larger operational structures in addition to specific jobs. According to Chu, hospitals must reconsider how everyday tasks are assigned in light of the incorporation of robots like Moxi.
Workflows are altered in many institutions such that the robot is integrated into the daily team structure and receives automatic requests from central supply units or electronic health record systems. Because of this integration, the robot can operate as a dependable logistical helper whose performance is consistent during shifts and staffing shortages. The provision of robotic help is crucial in balancing workflow demands as hospitals deal with growing patient numbers and pressing manpower issues. Moxi’s presence has affected employees’ perceptions of automation in addition to its immediate workflow benefits. According to Chu, many hospital staff members are initially curious about the robot but soon come to view it as a trustworthy instrument.
“This shift frequently happens after the robot consistently performs jobs like delivering prescription drugs, moving machinery, or replenishing supplies. Staff members start to delegate more regular jobs to the robot as they become more confident in its dependability, which improves operational flow and makes better use of human experience in patient care.”
By highlighting the benefits of socially conscious robots, human-robot cooperation also has an impact on the larger robotics sector. Dr. Chu’s work with Diligent Robotics demonstrates how human-centered environments are more likely to embrace robots with expressive, predictable behavior. This design approach signifies a move away from conventional industrial robots and toward systems that place an emphasis on anticipating, communication, and peaceful human interaction. These characteristics are crucial to guaranteeing that automated systems can help people safely and effectively as robots become more prevalent in places like hospitals, schools, hotels, and transportation hubs.
Furthermore, Chu’s focus on predictive modeling represents a significant advancement in technology. Compared to systems that merely react to current sensory data, robots that can predict patterns such as busy hallways, equipment movement, or regular staff schedules offer operational advantages. Robots with predictive capabilities can decrease delays, avoid bottlenecks, and navigate more effectively. These advancements show how service robots is likely to develop and increase overall productivity. the results of Chu’s research, as robots advance in capability, social awareness, and integration into workplace infrastructure, human-robot collaboration will likely continue to grow.
The global robotics market has seen a slew of growth in the last few years. Businesses are debating where the ceiling is in a few years, some predicting will market will surpass $240 billion by 2032 while others see it more modestly at $90 billion. The market is already on its way, as service robotic sales were $40 billion in 2023 and growing by 15 percent every year, according to International Federation of Robotics.
Companies are predicted to stay competitive in manufacturing, automation will be key to staying competitive. But in healthcare, a predicted shorting nursing in the upcoming years may turn to more reliance on robotics, notably to complete non-shift and administrative taks.
Larger fleets of robots that coordinate tasks, dynamically adjust routes, and communicate via shared information systems are anticipated to be used by hospitals. Robots’ models will get more complex as they gather more operational data, enabling them to support a wider variety of jobs and more precisely predict human demands. These robots’ operations will be governed by the ongoing development of safety standards and legal frameworks, guaranteeing consistency and dependability in settings where human welfare is paramount.
In the end, the development of robots such as Moxi is a reflection of the larger trend of using automation to supplement human capabilities rather than to replace them. Dr. Vivian Chu’s contributions to the field show how robotics can help vital industries, especially healthcare, by increasing workflow efficiency, lowering staff workloads, and proving that well-designed robots can successfully work alongside people in demanding, human-centered environments.
