Robot Autonomy and the Future of Robotic Inspection Systems
Overview
The world is rapidly entering the era of automation, with robots in the forefront of this transformation. This guide explores how the autonomy of robotic systems, particularly in the context of inspections, is shaping the future. It uncovers aspects such as the future market of robots, talent shortage and training, evolution and improvements in autonomy, and the role of AI and machine learning in robotics. It will present key statistics illustrating the surge in robot implementation for various use cases. Lastly, we’ll review the innovative work of 3Laws Robotics to address critical concerns related to safety, reliability, and the certification of robotics.
The Future Market of Robots
According to MarketWatch, the global industrial robotic market is projected to expand at a CAGR of 11.5% from 2021 to 2026. In particular, the robotic inspection market is expected to grow significantly, given its role in ensuring quality and consistency in various sectors. Analysts predict that the adoption of robotic inspection systems will save approximately 20% of costs associated with manual inspections, driving cost efficiency and operational optimization.
Talent Shortages and Training
Despite the rapid advancements in robotics, businesses continue to face significant talent shortages in operating and maintaining these systems. Challenged with the need for effective and efficient onboarding, companies are seeking solutions that can simplify this process. An estimated 64% of businesses reportedly mention a lack of qualified staff as a barrier to implementing robotic systems.
Evolution and Improvement in Autonomy
The levels of autonomy in robotic systems have significantly improved over the past few years. Robots are no longer restricted to repetitive tasks and programmed operations; they are equipped with sensing and cognitive abilities. Currently, about 50% of factory robots have a high level of autonomy, enabling them to function independently, make decisions, and adapt to changing situations.
Role of AI and Machine Learning in Robotics
Artificial Intelligence (AI) and machine learning (ML) are playing a crucial role in broadening the scope of robot autonomy. With AI and ML, robots can process substantial amounts of data, learn from their surroundings and improve their performance over time. It is expected that by 2025, over 70% of robots in use will be AI-enabled, driving even greater efficiencies and possibilities in various industries.
Key Takeaways
• The global market of robotic inspection systems is expanding rapidly, promising cost reductions and optimization of operations.
• Businesses face talent shortages in the field of robotics, necessitating more simplified and user-friendly systems.
• The level of autonomy in robotic systems has significantly increased, with about half of current factory robots functioning independently.
• Artificial Intelligence and machine learning are broadening the applications of robots, with 70% of robots expected to be AI-enabled by 2025.
3Laws Robotics: Enhancing Safety and Reliability in Robotic Systems
3Laws Robotics is in the innovative forefront of addressing key industry challenges such as safety, reliability, and certification difficulties for robotic systems. The company’s software - 3Laws Supervisor - is geared to simplify the certification process by ensuring system robustness and robust safety features. Built on Control Barrier Functions, a technology developed at Caltech, the software provides mathematically provable safety.
3Laws' technology has a broad spectrum of applications in various industries. In warehouse automation, it has resulted in a 40% efficiency gain and a six-month payback period for an autonomous forklift customer. In the realm of human-robot interactions, it can ensure safe and uninterrupted operation near humans, a growing requirement for collaborative robotics solutions. Furthermore, its reactive collision avoidance capabilities make it an essential tool for robots operating in dynamic environments.
Beyond safety, 3Laws' software also enhances operational efficiency by minimizing downtime, enabling robots to operate near their peak capabilities without compromising safety. Adaptable to a wide range of platforms - from mobile robots, cars, to drones and manipulators - and compatible with popular robotics middleware like ROS and ROS2, it stands as a next-gen safety solution, surpassing traditional e-stop methodologies. In essence, it offers proactive safety and unlocks the full potential of robotics with dynamic, predictive safety, feasible for safety certification under ISO 3691-4 and ISO 26262.