Rodney Brooks (Rethink Robotics Co-founder) – Robotics Innovation Challenge 2012 (2012)

Chapters

Abstract

Bridging the Gap: The Evolving Landscape of Robotics and Its Multifaceted Challenges

In the rapidly evolving field of robotics, the intersection of technological advancements, societal demands, and business model explorations presents both unprecedented opportunities and complex challenges. Labor shortages and the aging population are fueling the demand for robotic solutions in manufacturing, healthcare, and elder care. Meanwhile, Rodney Brooks, founder of iRobot Corporation, highlights the computational challenges in robot perception and the intricacies of developing successful business models, as evidenced by iRobot’s journey through 14 failed attempts before hitting success with the Roomba. The industry also grapples with the difficulty of assessing the complexity of robotic systems, unpredictable market responses, and the limitations of traditional engineering approaches. This article delves into these multifaceted aspects, emphasizing the unique challenges in robotics investment, the significant gap between human and robot perception, and the contrasting reward systems of academia versus industry, all while considering the potential for impactful collaboration between these two spheres.

1. Demands for Robotics Solutions: Addressing Societal Needs

The growing need for robotics is largely driven by a labor shortage caused by an aging population and rising labor costs. Industries like manufacturing, healthcare, and elder care are increasingly relying on robots for automation. Technological advancements following Moore’s Law have enhanced sensors, actuators, and computation capabilities, while user interface developments are making it easier for non-experts to interact with and control robots, expanding their potential applications.

Economic factors, such as rising labor costs, also contribute to the demand for robots, making them a cost-effective solution for businesses facing labor shortages. Additionally, the aging population in many countries is leading to a greater need for robots in industries like elder care and healthcare.

2. Societal Impacts of Robots: From Homes to Battlefields

Robots have made significant inroads across various sectors. Their use ranges from military operations for tasks like bomb disposal and surveillance, to household chores through devices like vacuum cleaners and lawnmowers. In the industrial sector, robots undertake repetitive and hazardous tasks, boosting productivity and safety. In healthcare, their role is expanding into surgery assistance, rehabilitation therapy, and medication delivery, showcasing their versatility and impact on daily life.

Beyond the mentioned applications, robots have played crucial roles in challenging situations, such as the mapping of the oil boom during the BP oil disaster in the Gulf of Mexico and the cleanup efforts at the Fukushima power plant after the 2011 earthquake and tsunami in Japan.

3. Challenges in Robotics Investment: Navigating a Complex Landscape

Investing in robotics is fraught with challenges. The complexity and rapid evolution of the field make it difficult to assess the technical feasibility and market potential of robotic solutions. Investors face unpredictability in market response and are often challenged by the limitations of conventional engineering methods, which struggle to address the multifaceted nature of robots. These factors necessitate a cautious and informed approach to investment in the robotics sector.

Compounding these challenges is the difficulty in assessing the complexity of robot tasks and predicting market receptiveness to new solutions. Conventional top-down engineering approaches often don’t work well for robots due to their complexity and interactive nature.

4. Perception in Robotics: The Computational Challenge

Rodney Brooks emphasizes the significant gap between human perception and robot capabilities. He points out that tasks easy for humans, like visual perception, are computationally challenging for robots. This disparity is often masked by science fiction and lab demonstrations, which set unrealistic expectations. The complexity of robot perception is exemplified by the challenges in interpreting visual information, a task effortlessly performed by the human brain but greatly complex for robots.

Perception is a key challenge in robotics, as current robotic perception systems are not very good at handling complex real-world scenarios. 3D data alone is not enough to solve the perception problem; computational processing is also crucial.

5. Business Models in Robotics: Lessons from iRobot’s Journey

Brooks’ experience with iRobot highlights the trial-and-error nature of developing successful business models in robotics. The company’s journey through 14 failed models before finding success with the Roomba underscores the importance of timing, luck, and market receptiveness in the robotics industry. This journey also reflects the unpredictable nature of market dynamics, as seen in the fluctuating demand for specialized robots like those for nuclear power plant inspection.

Brooks’ insights on business models in robotics extend beyond iRobot’s journey. Timing and luck play a significant role in the success of a business model, and the journey from idea to product requires significant effort and resources. Additionally, sales and marketing are crucial for the success of a product.

6. Engineering Challenges in Robotics: Beyond Conventional Approaches

Robotics presents unique engineering challenges, differing significantly from traditional disciplines. Robots operate in dynamic environments, necessitating adaptability and real-time decision-making. This contrasts with more controlled environments like those for airplanes. Furthermore, commercial robots require robustness and reliability, demanding meticulous engineering and extensive testing, a step beyond the scope of lab prototypes.

Robotic engineering is inherently harder than other types of engineering due to the complex and continuously changing environments that robots must operate in. Additionally, it is difficult to predict whether a laboratory prototype can be turned into a robust system suitable for commercialization.

7. Strategies for Impact: Academic Research in the Real World

Brooks offers practical advice for academics aiming to translate research into real-world applications. He emphasizes the importance of moving beyond mere hope for research adoption and suggests active engagement with commercial sponsors and the potential of starting companies around innovative ideas. His “90-10-90 Rule” underlines the extensive effort required to turn a concept into a commercially viable product.

Despite the difficulties in translating academic research into real-world applications, there are strategies that academics can employ. These include collaborating with commercial sponsors, consulting for companies, and starting companies around innovative ideas.

8. Academia vs. Industry: Divergent Reward Systems

The contrasting reward systems in academia and industry significantly impact the development and application of robotics. Academia values the novelty and elegance of ideas, whereas industry prioritizes customer value and practicality. This difference often leads to a disconnect between academic research and its practical application in commercial products.

The differing priorities between academia and industry can lead to challenges in communication and collaboration. Engineers in industry may not have the time or interest to read scientific papers shared by academics, leading to a lack of understanding. Additionally, CEOs may perceive academics as having contempt for customers and being unwilling to compromise.

9. Industry-Academia Collaboration: Overcoming Barriers

Collaboration between industry and academia faces several hurdles, including communication barriers and differing objectives. Academic demonstrations are often tailored for success, whereas industry applications require cost-efficiency and reliability. Bridging these gaps requires addressing specific design specifications and focusing on customer satisfaction over technical prowess.

Despite the challenges, industry-academia collaboration can be beneficial for both parties. Academics can gain insights into the practical needs of industry, while industry can access cutting-edge research and innovative ideas. To facilitate successful collaboration, it is important to address communication barriers and ensure that both parties have a clear understanding of the project goals.

10. Opportunities for New Companies: Filling the Gap

The challenges in industry-academia collaboration open doors for new companies that can bridge this divide. These companies can play a pivotal role in translating academic research into practical applications, thus fostering innovation and addressing real-world needs in the robotics sector.

The gap between academic research and industry needs presents opportunities for new companies to emerge. These companies can leverage academic research to develop innovative products and services that address real-world problems. By bridging the gap between academia and industry, these companies can drive innovation and contribute to the advancement of the robotics sector.

Navigating the Robotics Frontier

The robotics industry stands at a pivotal point, marked by significant growth potential and complex challenges. Balancing the demands for technological innovation with practical application, and aligning academic research with industry needs, are critical for the sustainable development of the robotics field. As the industry navigates these challenges, the potential for impactful advancements in robotics remains immense, promising transformative changes across various sectors of society.

Notes by: Flaneur