Overcoming Challenges in Robotic Automation with CapSen PiC

Introduction

Although robotic automation in industrial processes has been around for decades, its demand has only recently skyrocketed across industries. The pursuit of greater efficiency, precision, and cost savings primarily drives this growth. Additionally, a significant factor behind this trend is the persistent labor shortage in manufacturing and other industrial sectors.  According to the National Association of Manufacturers, nearly 2.1 million manufacturing jobs could go unfilled by 2030 due to a lack of skilled workers. This workforce gap is pushing companies to adopt automation at an accelerated pace. This workforce gap has accelerated the adoption of automation as businesses seek innovative solutions to maintain productivity.

In fact, the global robotics market is projected to reach $50.8 billion by the end of this year, with a compound annual growth rate (CAGR) of 9.49%.  

The Importance of Robotic Automation in Handling Diverse and Complex Tasks

Robotic automation is crucial for managing complex and diverse tasks, boosting efficiency and precision in manufacturing, logistics, and healthcare industries. Robots excel at repetitive, high-accuracy operations and can adapt to handle varying complexities. This capability reduces human error, streamlines workflows, and ensures scalability, effectively meeting the demands of modern industries.

Common Challenges in Robotic Automation

Some of the key challenges that hinder efficiency and the adoption of robotic process automation are as follows:

1. Achieving precision and accuracy in robotic process automation is critical, especially for tasks requiring consistent, high-precision movements. However, external factors like mechanical imperfections or environmental disturbances often pose difficulties. For example, for tasks like assembly, welding, or quality inspection, robotic systems must operate with exceptional precision and repeatability. However, factors like mechanical wear-and-tear, sensor calibration issues, and external disturbances (e.g., vibrations or changes in lighting conditions) can compromise performance. Overcoming these issues requires robust calibration, high-quality components, and advanced control algorithms to ensure consistent outputs despite environmental variability.

2. Ensuring flexibility and versatility is challenging, as robots often struggle to adapt to diverse object shapes, sizes, and materials. Traditional robots are often programmed for repetitive tasks involving uniform objects, making them less effective when dealing with diverse shapes, sizes, or materials. For instance, sorting irregular items like tangled wires or varying package sizes demands a high level of adaptability. By integrating AI-powered vision systems and grippers with specialized end-effectors, robots can gain the capability to handle complex, dynamic scenarios. However, developing and fine-tuning these systems is resource-intensive.

3. Integration into legacy systems can be complex, with older infrastructure often incompatible with modern robotics. Many manufacturing facilities still rely on legacy systems that were not designed with modern robotics in mind. Integrating robotic automation into such setups involves technical challenges, such as compatibility issues with existing hardware and software. Retrofitting these environments often requires custom middleware, modular robot designs, and financial investments. Successful integration demands a balance between leveraging new technologies and preserving the functionality of existing systems to minimize downtime.

4. For many businesses, cost-effectiveness remains a significant hurdle in adopting robotics. High upfront costs, including purchasing, installation, and training, can deter investment, especially for smaller companies. However, scalable and modular robotics are emerging as practical alternatives. These systems allow businesses to start small and expand their automation gradually, reducing initial financial strain while delivering long-term returns on investment.

5. Robots must also tackle real-world variations, such as disorganized or unpredictable environments. AI-powered vision systems enable robots to dynamically adjust to these conditions, improving their performance in non-linear, cluttered, or fast-changing scenarios, such as sorting irregularly shaped objects or navigating crowded spaces.

6. Lastly, safety in human-robot interactions is a vital consideration as automation becomes more integrated with the workforce. Robots equipped with force-limiting mechanisms can detect and respond to physical contact, reducing the risk of injury. Robust safety protocols, such as defined collaborative zones and advanced sensors, help create a safe, efficient environment where robots and human workers can operate in harmony.

Overcoming these challenges is key to fully realizing the potential of robotics, enabling industries to achieve greater efficiency, precision, and adaptability in a rapidly changing world. Let me know if you'd like me to expand even further!

How CapSen PiC Addresses These Challenges

CapSen PiC provides superior performance compared to other similar software in terms of speed, variety of objects, vision and detection, possible applications, and motion planning capabilities.

PiC performs consistently well across categories, while some other bin-picking software has limited speed, vision, or motion planning capabilities. Our system's motion planning algorithms ensure collision avoidance between the robot, the bin-picking cell, and objects and end effectors. It can even perform advanced motion planning tasks such as detangling and assembly. Image processing and planning times of under a second make it the fastest software on the market, enabling PiC-powered cells to pick and place up to 30 parts per minute.

Other than pick-and-place, our software can also handle tasks like machine tending, kitting and sorting, tote handling, repacking, palletizing, and depalletizing.

CapSen PiC is hardware agnostic, thus allowing integration with any robotic arm and camera. This makes the integration of existing systems quite seamless while curtailing excessive costs. 

Real-World Applications of CapSen PiC

Vision-guided Cobot Automates Paint Process for DENSO

Among the various complex production processes in the automotive manufacturing industry, a number of them are tedious and difficult to be accomplished safely and accurately by human workers. Implementing robotic automation systems can greatly benefit such processes, adding value to the businesses. One such example was a repetitive and physically challenging tote-handling task that DENSO- a leading global automotive parts manufacturer sought to automate.

So the idea was to use robots instead of the employees to load and unload large stacks of heavy totes to and from a paintbooth. DENSO partnered with CapSen Robotics to implement customized 3D vision, motion planning, and control software to handle this task.

The CapSen PiC 2.0 software, running on an industrial PC with a graphics processing unit (GPU), allows the robot to plan its motion, locate, pick up, and manipulate the tote and move it toward another conveyor headed to the paint booth station. There, the parts are unloaded, painted, put into an oven for curing, and inspected before being put back into the totes and onto the conveyor going back toward the robot, which identifies the tote and places it onto an outbound conveyor.

Read more about this solution here.

A Robot Untangles Metallic Spaghetti

Ace Wire Spring & Form Co. Inc. is a leading maker of custom springs and wire forms, including metal wire that is formed into hooks, based in Pittsburgh. The manufacturing procedure for these hooks is highly complex, requiring 10 steps in the hook production process. This begins with bending the wire into 5 cm hooks, passing these hooks as bulk material into bins, and then inserting them into a press to form the ends. After pressing, operators put a bead on the flattened end of the hook at another station, and then the bead and the hook are pressed together with a spring. The final product is a swivel hook extension spring that is used as a tensioning spring for fan belt pulleys.

A crucial part of this production process is picking up a single hook from an entangled mass- a task that was originally performed manually. While this is a classic bin-picking problem, the entanglement of the hooks made it more complex than usual. Imagine trying to pick a single strand of spaghetti from a plate- the robot needed to do something similar with metals.

The process automation of untangling one hook from the jumbled pile began with proprietary 3D vision algorithms combined with classical geometric CAD matching techniques and modern machine learning methods. This combination offered high detection accuracy across a wide range of object shapes, sizes, and materials.

CapSen Robotics designed and implemented a bespoke solution to allow robots to pick these hooks out of the bins, detangle them, and place them into the press.  A key factor in providing the robot with the necessary spatial intelligence to manage the process was CapSen Robotics Inc.’s complete solution, which includes 3D vision, full motion planning, and control software.

You can read more about this particular solution here.

The Future

The field of robotic automation is currently being transformed by advanced solutions that combine various capabilities to enable smooth manipulation across industries. Emerging trends include open-source frameworks and collaborative robots (cobots) designed to enhance human-robot interaction. Future advancements in AI and machine learning will continue to improve adaptability, allowing robots to perform increasingly complex and precise tasks. These innovations are driving widespread adoption, revolutionizing industries, and elevating automation to unprecedented levels.

At CapSen Robotics, we work closely with businesses to help them automate their processes to achieve better efficiency while improving ROI. Get in touch with us today to learn more about how CapSen PiC can transform your automation journey.