BotsAndUs releases “seminal” white paper

“The use of Industrial Internet of Things (IIoT) technologies allows warehouses to become better at managing and performing a multitude of tasks, improve the operational efficiency by huge margins. They have real-time data transfer, flexible communication, and Big Data analytics. These, along with the cloud-based solution, enable automated, sophisticated, and agent-based control.”

These are the insights shared by British AI, Data and Robotics company BotsAndUs in its seminal White Paper –  Robotics And Automation: A Revolution In Logistics And Warehouse Management – that clearly lays out the business case for the use of AI and robotics solutions in logistics and warehouse management.  As the industry knows at a great cost, limited visibility of the goods’ journey affects every step and stakeholder within the supply chain. Robotics and AI introduce a total visibility of the good’s journey, together with cost-efficiencies, improvements in processes and optimisation of operations.

In recent years, the logistics and warehouse markets have experienced unprecedented growth. This was mostly driven by the surge in e-Commerce in response to the pandemic and restrictions, as well as by the industry’s need for efficient warehousing, inventory management and real time data to deliver efficiencies and cost savings. Across the supply chain there are challenges in stock changes, shortages in workforce, issues with deliveries and a rise in overall costs. In addition, billions of pounds are lost annually due to the lack of real time data on warehouse operations and crucial logistics nodes.

Coupled with other major concerns that include the ability to quickly identify and act on problems in the warehouse, logistics and wider supply chain early on, it is easy to see why the industry is looking for solutions.

BotsAndUs is a London-based data-driven technology company using artificial intelligence, autonomous systems and robotics. It is transforming the logistics industry through automation and real time digitisation of assets. Its White Paper explains the technology and allays the concerns – and myths – that are worrying operators of logistics and warehouses in the UK.

Oana Jinga, BotsAndUs Co-Founder commented on the White Paper, saying: “The release of our White Paper – Robotics And Automation: A Revolution In Logistics And Warehouse Management – coincides with an increased demand from the industry for practical and cost-effective solutions. At first glance, it would appear that the only way for companies to ease these pressures will be to introduce big changes to the way they operate along the supply chains.

“However, we know that automation in logistics and warehousing present immediate solutions and immense opportunities for early adopters in terms of more efficient processes and space optimisation, regardless of the size of their operations.”

Andrei Danescu, CEO and Co-founder continued: “At BotsAndUs, we are pioneers in this industry and we are building the next generation of AI and robotics technology to help organisations harness the power of real-time data and become more efficient in driving their operations. We have developed autonomous technology that works alongside logistics and warehouse employees. The technology focuses on data capturing and automation through fleets of autonomous robots that scan the entire warehouse, building up data for a digital twin for real-time analysis and insights on storage of goods in warehouse space.

“This then feeds into optimisation programmes. There is no workflow disruption at any stage. The data-gathering robot accelerates productivity, reduces unnecessary time spent processing and tracking and allows businesses to drive better business decisions.”

The White Paper features a clear explanation of this technology and how it can be delivered across the logistics and warehouse operations. The White Paper may be collected/retrieved from the BotsAndUs stand #8045 at Multimodal.

BotsAndUs uses artificial intelligence, autonomous systems and robotics to transform the logistics industry through automation and real time digitisation of assets. Founded in 2015, its state-of-the-art robotics and AI products combine social sciences with human-centred design and cutting-edge engineering. Mim, its fully autonomous mobile and modular robot measures, tracks and finds goods across warehouses without workflow disruption and provides real time data at every stage of the process.

Tompkins-GRS partnership yields RaaS model

Tompkins Robotics, a global leader in the robotic automation of distribution and fulfilment operations, has partnered with Global Robotics Services (GRS), a GLP backed platform that provides financial backing for collaborative robots as a service (RaaS) solutions.

The Tompkins Robotics – GRS RaaS solution provides customers with the ability to pay for what they consume including equipment, installation, commissioning, and support costs, all of which are included in the service level agreement (SLA). This innovative model gives customers the flexibility of a subscription-based pricing and service option instead of traditional capital equipment purchase and support model. This conserves capital, converts investment to an operating cost, and allows a customer to “pay as they go” for the use of the system.

RaaS also provides customers with the ability to scale up and down rapidly and easily in response to changing market conditions or seasonal demand such as the Holiday season, Back to School, January returns, and other seasonal events.

Tompkins Robotics, with its tSort robotic solution, has developed a reputation for execution of projects, rapid deployment, scalable layout design, understanding of US building codes, and knowledge of logistics operations. GRS brings the financial strength and resources of a global logistics real estate investor, developer, and operator. Together, Tompkins Robotics and GRS will bring new opportunities for US companies easy entry into automation and robotics.

Mike Futch, CEO of Tompkins Robotics, said: “The asset services support from our partnership with GRS will position Tompkins Robotics to implement a RaaS deployment for customers that prefer this model versus our existing capital procurement business model. In addition, our solutions have always had a reputation for being flexible, now we have the opportunity to allow financial flexibility as well.”

Hongming Chen, CEO of GRS, added: “Our vision is to accelerate the adoption of automation while lowering the barrier to entry for businesses when it comes to robotics technology. The subscription-based model of RaaS creates lower upfront capital requirements, reduced fixed costs and flexible lease terms which helps bridge the automation gap for many small to mid-size enterprises.

“A full package of services including consulting, implementation, maintenance, systems and robotics upgrading can all be provided as part of this service. With both parties expertise and resources, we look forward to expanding our cooperation with Tompkins in greater depth and breadth to provide a more holistic solution to our customers.”

 

Autonomously picking robot relies on cutting-edge solution

Due to the industry standard 4.0, digitalisation, automation and networking of systems and facilities are becoming the predominant topics in production and thus also in logistics. Industry 4.0 pursues the increasing optimisation of processes and workflows in favour of productivity and flexibility and thus the saving of time and costs. Robotic systems have become the driving force for automating processes.

Through the Internet of Things (IoT), robots are becoming increasingly sensitive, autonomous, mobile and easier to operate. More and more they are becoming an everyday helper in factories and warehouses. Intelligent imaging techniques are playing an increasingly important role in this.

To meet the growing demands in scaling and changing production environments towards fully automated and intelligently networked production, the company ONTEC Automation GmbH from Naila in Bavaria has developed an autonomously driving robotic assistance system. The “Smart Robot Assistant” uses the synergies of mobility and automation: it consists of a powerful and efficient intralogistics platform, a flexible robot arm and a robust 3D stereo camera system from the Ensenso N series by IDS Imaging Development Systems GmbH.

#The solution is versatile and takes over monotonous, weighty set-up and placement tasks, for example. The autonomous transport system is suitable for floor-level lifting of Euro pallets up to container or industrial format as well as mesh pallets in various sizes with a maximum load of up to 1,200kg. For a customer in the textile industry, the AGV (Automated Guided Vehicle) is used for the automated loading of coil creels.

For this purpose, it picks up pallets with yarn spools, transports them to the designated creel and loads it for further processing. Using a specially developed gripper system, up to 1,000 yarn packages per 8-hour shift are picked up and pushed onto a mandrel of the creel. The sizing scheme and the position of the coils are captured by an Ensenso 3D camera (N45 series) installed on the gripper arm.

Pallets loaded with industrial yarn spools are picked up from the floor of a predefined storage place and transported to the creel location. There, the gripper positions itself vertically above the pallet. An image trigger is sent to the Ensenso 3D camera from the N45 series, triggered by the in-house software ONTEC SPSComm. It networks with the vehicle’s PLC and can thus read out and pass on data.

In the application, SPSComm controls the communication between the software parts of the vehicle, gripper and camera. This way, the camera knows when the vehicle and the grabber are in position to take a picture. This takes an image and passes on a point cloud to a software solution from ONTEC based on the standard HALCON software, which reports the coordinates of the coils on the pallet to the robot.

The robot can then accurately pick up the coils and process them further. As soon as the gripper has cleared a layer of the yarn spools, the Ensenso camera takes a picture of the packaging material lying between the yarn spools and provides point clouds of this as well. These point clouds are processed similarly to provide the robot with the information with which a needle gripper removes the intermediate layers.

“This approach means that the number of layers and finishing patterns of the pallets do not have to be defined in advance and even incomplete pallets can be processed without any problems,” explains Tim Böckel, software developer at ONTEC. “The gripper does not have to be converted for the use of the needle gripper. For this application, it has a normal gripping component for the coils and a needle gripping component for the intermediate layers.”

For this task, the mobile use for 3D acquisition of moving and static objects on the robot arm, the Ensenso 3D camera is suitable due to its compact design. The Ensenso N 45’s 3D stereo electronics are completely decoupled from the housing, allowing the use of a lightweight plastic composite as the housing material. The low weight facilitates the use on robot arms such as the Smart Robotic Assistant.

The camera can also cope with demanding environmental conditions. “Challenges with this application can be found primarily in the different lighting conditions that are evident in different rooms of the hall and at different times of the day,”

Tim Böckel describes the situation. Even in difficult lighting conditions, the integrated projector projects a high-contrast texture onto the object to be imaged by means of a pattern mask with a random dot pattern, thus supplementing the structures on featureless homogenous surfaces. This means that the integrated camera meets the requirements exactly.

“By pre-configuring within NxView, the task was solved well.” This sample programme with source code demonstrates the main functions of the NxLib library, which can be used to open one or more stereo and colour cameras whose image and depth data are visualised. Parameters such as exposure time, binning, AOI and depth measuring range can – as in this case – be adjusted live for the matching method used.

The matching process empowers the Ensenso 3D camera to recognise a very high number of pixels, including their position change, by means of the auxiliary structures projected onto the surface and to create complete, homogeneous depth information of the scene from this. This in turn ensures the necessary precision with which the Smart Robot Assistant proceeds. Other selection criteria for the camera were, among others, the standard vision interface Gigabit Ethernet and the global shutter 1.3 MP sensor.

“The camera only takes one image pair of the entire pallet in favour of a faster throughput time, but it has to provide the coordinates from a relatively large distance with an accuracy in the millimetre range to enable the robot arm to grip precisely,” explains Matthias Hofmann, IT specialist for application development at ONTEC.

“We therefore need the high resolution of the camera to be able to safely record the edges of the coils with the 3D camera.” The localisation of the edges is important in order to be able to pass on as accurate as possible the position from the centre of the spool to the gripper. Furthermore, the camera is specially designed for use in harsh environmental conditions. It has a screwable GPIO connector for trigger and flash and is IP65/67 protected against dirt, dust, splash water or cleaning agents.

The Ensenso SDK enables hand-eye calibration of the camera to the robot arm, allowing easy translation or displacement of coordinates using the robot pose. In addition, by using the internal camera settings, a “FileCam” of the current situation is recorded at each pass, i.e. at each image trigger.

This makes it possible to easily adjust any edge cases later on, in this application for example unexpected lighting conditions, obstacles in the image or also an unexpected positioning of the coils in the image. The Ensenso SDK also allows the internal camera LOG files to be stored and archived for possible evaluation.

ONTEC also uses these “FileCams” to automatically check test cases and thus ensure the correct functioning of all arrangements when making adjustments to the vision software. In addition, various vehicles can be coordinated and logistical bottlenecks minimised on the basis of the control system specially developed by ONTEC.

Different assistants can be navigated and act simultaneously in a very confined space. By using the industrial interface tool ONTEC SPSComm, even standard industrial robots can be safely integrated into the overall application and data can be exchanged between the different systems.

Further development of the system is planned, among other things, in terms of navigation of the autonomous vehicle. “With regard to vehicle navigation for our AGV, the use of IDS cameras is very interesting. We are currently evaluating the use of the new Ensenso S series to enable the vehicle to react even more flexibly to obstacles, for example, classify them and possibly even drive around them,” says Tim Böckel, software developer at ONTEC, outlining the next development step.

ONTEC’s own interface configuration already enables the system to be integrated into a wide variety of Industry 4.0 applications, while the modular structure of the autonomously moving robot solution leaves room for adaptation to a wide variety of tasks. In this way, it not only serves to increase efficiency and flexibility in production and logistics, but in many places also literally contributes to relieving the workload of employees.

ONTEC Automation GmbH is a system provider for integrated and innovative automation systems, plants and special machines for industrial production. The business units consist of Technical Textile Solutions, Automation Solutions, Smart Robotic Solutions and Electric Switchboard Solutions.

The company’s expertise with 25 years of experience is reflected in innovative, customer-oriented solutions along the entire value chain and includes robotics, industrial image processing, software development, electrical engineering and mechanics.

 

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