System and method for transporting materials using transporters guided by smart guided vehicle

Abstract

A master smart guided vehicle (SGV) equipped with an intelligent module for precisely locating and positioning a set of transporters dynamically assigned to transfer a load accurately and safely from one location to another. The SGV may comprise of Vision modules, a feed forward control method that uses sensors to detect disturbances or obstructions affecting the transporter movements and apply a feedback control input to the SGV to minimise the effect of the disturbance. Path planning software modules and artificial intelligence are utilised in the SGV to understand the environment it is operating in, and function independently without depending upon external instructions. The smart guided vehicle plays an important role in efficient material handling within a manufacturing and distribution operation. The material handling functions are performed safely and in a timely manner without causing any damage to the payload irrespective of its size and weight. The main factor attributing to material handling is reliability, consistency and dynamic workload distribution with minimal intervention from an external command centre such as a server or other device. Smart Guided Vehicle is controlled by intelligent software reinforced with Machine learning techniques that optimise workflows by automating repetitive material handling tasks, reducing bottlenecks by utilising the services of multiple transporter modules depending upon the task to be executed.

Description

[0001] SYSTEM AND METHOD FOR TRANSPORTING MATERIALS USING TRANSPORTERS GUIDED BY SMART GUIDED VEHICLE

[0002] Filed of the Invention

[0003] The present disclosure generally relates to smart guided vehicles (SGVs) and, more particularly, to the system and method of an SGV working independently to manage a plurality of transporters to perform multiple tasks in a variety of industrial environments.

[0004] Background

[0005] Smart guided vehicles may be used to command transport robots otherwise called transporters to move payloads along a predetermined route without real-time human intervention. For example, an SGV can command the transporters to move items such as heavy vehicle components like engines, chassis, automotive components, precision parts etc, along a route in a manufacturing plant floor to deliver the payload from one location to another for various operations to be performed thereon. The transporters in conjunction with the SGV may include stabilising mechanisms to traverse irregular surfaces, vision systems to identify items of interest, laser guidance for collision avoidance, sensors for path finding and alignment to enable movement of the payload speedily and efficiently. The SGV controls multiple transporters to enable transfer of material from more than one location to another within an industrial environment, while also offering the flexibility to dynamically reconfigure the origin and / or destination. By far the most pervasive materials-handling process within any industrial environment entails the use of transporters and intelligent guided vehicles combined into one. with commands coming from an external server that continuously monitors the movements of every transporter and guides them accordingly from one location to another. The reliance on external servers increases execution time due to extensive data exchange between transporter and server to achieve an appropriate route path that is accurate and collision free.

[0006] SGVs may offer the ability to control multiple transporters to carry payloads too heavy, dangerous or bulky, for a person to carry while also offering the flexibility to be reconfigured to follow a different route or carry different types of payloads, all within the industrial environment with little or no communication with an external server.

[0007] Summary of Invention

[0008] In a first aspect, the Invention provides a localised payload moving system comprising: a smart guided vehicle (SGV). comprising: a multidirectional motorised module that behaves as a guiding system with ability to move in any direction; at least one omnidirectional camera to capture images for a 360 view; a vision system to process images and detect objects around it for the control system to determine the pathways for the transporters; communicating electronics such as WiFi & Bluetooth for sending and receiving data; sensors to detect nearby objects and obstructions in real time in combination with thermal sensors, lasers, radars & movement detectors; a high capacity Li-ion battery capable of operating continuously for long periods of time with minimum charging intervals; at least a pair of transporters comprising: communicating electronics such as Wifi, Bluetooth for sending and receiving data; sensors to detect nearby objects and obstructions in real time in combination with thermal sensors, lasers, radars, movement detectors and gyro sensors; a set of force torque sensors using strain gauges to measure weight of the payload; proportional integral derivative (PID) controllers for closed loop control of speed and position and angular trajectories to avoid resonant modes in transporters; a platform mounted on the top for lifting the payload and mechanically integrated with a lifting mechanism; a set of weighing gauges to measure the weight of the payload and communicate the data to the SGV; a high capacity Li-ion battery capable of operating continuously for long periods of time with minimum charging intervals.

[0009] In a second aspect, the Invention provides a localised payload moving method comprising: the smart guided vehicle receiving a command from a central master wirelessly and calculating the path from the source and destination based on the payload weight; utilising built in Al tools combined with machine learning models and incorporated with reinforced learning tools to achieve optimal trajectory paths for speedy and efficient movement of the payload; reinforced learning tools that fine tune intelligent operating models based on historical data to improve path predictions resulting in optimum use of industrial space; creating a virtual view of the operating environment through a technique called SLAM (Simultaneous Localization and Mapping) by employing sensors and vision based systems with a 360 degree view of the working environment; Model Predictive Control (MPC) with the ability to anticipate future events and take control actions accordingly to avoid collisions and stoppages when unusual situations are encountered; ability to multitask in the form of sending instructions in parallel or in sequence to multiple transporters to control their speed, acceleration and angular stability for safe movement of die payload; capability to manage charging periods of the transporter Lithium ion batteries by the SGV, to ensure optimally charged transporters at any given time; an optimally charged SGV which manages itself to ensure no interruptions to the process. The following embodiments and aspects thereof are described and illustrated in conjunction with systems and methods that are meant to be exemplary and illustrative, not limiting in scope.

[0010] There is provided, in accordance with an embodiment, system comprising of a first SGV herein referred to as SGV and at least one transporter, the SGV programmed to dynamically configure a plurality of transporters to perform at least one servicing task such as moving the raw material or finished material between one or more of the plurality of multiple sites. Several SGVs may be deployed in the industrial environment depending upon the complexity of the tasks to be performed.

[0011] In one embodiment of the present invention, the system comprises: a multidirectional motorised guiding module known as the Smart guidance vehicle (SGV); at least a couple of transporters which perform the task of moving heavy payloads with complete guidance from the SGV; an array of sensors and peripherals incorporated in the SGV as well as the transporters, that include thermal sensors, lasers, radars, movement detectors, gyro sensors, vision system interacting with a set of full duplex communication transceivers either via a common bus or through Wifi, Bluetooth..etc.

[0012] The SGVs send guidance information for the routes of the transporters using a feed forward control method that utilises sensors to detect disturbances such as objects and obstructions in real time. The SGV also applies a feedback control input to minimise the effect of resonant modes that may cause vibration and instability. The SGV may also monitor surface characteristics of the determined route, angular trajectory of pathways to control the transporters when negotiating turns by reducing or increasing speed and acceleration, especially when moving heavy payloads. There is provided, in accordance with an embodiment, a method for autonomous interactions between the system of SGV and transporters, comprising an action of receiving a service command and subsequently computing the best-fit pathway or route for transferring the pay load from the original location to the destination. This is achieved through continuous reinforced learning of routes, trajectories, obstructions..etc and subsequently updating the knowledge database of optimised pathways for optimum performance.

[0013] Furthermore, the method also includes the action of determining the number of transporters required to move a payload that may be present within a container, box, carrier, tray, a wheeled trolley or any storage medium. Transporters are designed with weighing gauges to check the weight of the pay load and communicate the same to the SGV which in turn determines if more than one transporter is required to perform the task of moving the payload. The SGV subsequently communicates the determined pathways to the relevant transporters, and allocates the task accordingly.

[0014] The method further comprises an action of sending requests to nearby idle transporters to perform the transfer of pay loads.

[0015] The method further comprises an action of communicating signals and other data through multiple wireless channels such as Bluetooth, Wifi, 4G, to the allocated transporters.

[0016] The method further comprises an action of computing the fastest route to the destination, while avoiding collision with other transporters, SGVs or blockages along the route through an omnidirectional mirror to capture a 360 view of the working environment. An omnidirectional mirror integrated to a camera enables the creation of a panoramic view in real time, without the need for post processing commonly associated with conventional systems that capture multiple images of the surrounding environment and using computationally intensive algorithms, such as stitching the images together to create a panoramic view.

[0017] The method further comprises an action of sending commands to multiple transporters involved in picking up the payload at the source and releasing them at the destination asynchronously, without damaging the payload.

[0018] The method further comprises an action of sending commands to multiple transporters involved in picking up the payload at the source and transfer them to an intermediate location, wherein a different set of transporters may take over and move the payload from the intermediate location to the destination in the event the source and destination are very distant from each other. This process ensures a dedicated network of transporters working in a dedicated area instead of moving to very distant locations, making the logistic management of transporters simpler, faster and more efficient.

[0019] The method may further comprise an action of invoking a second SGV to take over the management of path planning for the transporters to free up the first SGV to perform other tasks, if such a situation occurs.

[0020] In addition to the exemplary aspects and embodiments described above, further aspects and embodiments will become apparent by reference to the figures and the following detailed description. Brief Description of Drawings

[0021] FIG 1 is an isometric view of an SGV;

[0022] FIG 2 is the Top view of the SGV in FIG 1;

[0023] FIG 3 is the Side view of the SGV in Fig 2;

[0024] FIG 4 is an isometric view of a transporter;

[0025] FIG 5 is the Top view of the transporter in FIG 4;

[0026] FIG 6 is tire Side view of a transporter in Fig 5 with the payload

[0027] lifting mechanism in the retracted position:

[0028] FIG 7 is the Side view of a transporter in Fig 6 with the payload

[0029] lifting mechanism in the extended position;

[0030] FIG 8 illustrates a typical manufacturing floor plan showing the location of raw materials and SGVs along with the supporting transporters. It also shows the workstations where the raw materials are loaded and unloaded for processing. Detailed Description of Drawings

[0031] The Smart guided vehicle (SGV) system described below may include multiple types of automated guided vehicles which are typically unmanned and self-propelled vehicles that travel in a dynamically programmed path based on the location of the material source and its destination on the floor of the industry, factory, warehouse, hospital, shopping mall, distribution centre..etc. Some examples of potential SGV applications include handling materials, delivering parts in a warehouse, moving a work piece or assembly through multiple workstations, delivering highly sensitive items in a clean room, medicines delivery in hospitals, old age caring homes..etc.

[0032] Elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions and / or relative positioning of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of various gadgets in the. present invention. Also, common but well-understood elements that are useful or necessary in a commercially feasible embodiment are often not depicted in order to facilitate a less obstructed view of the present invention. Certain actions and / or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually a standard. The terms and expressions used herein have the ordinary technical meaning as is accorded to such terms and expressions by a skilled person in the technical field as set forth above except where different specific meanings have otherwise been set forth herein.

[0033] Skilled artisans will appreciate that there are a number of different types of SGVs, including those that use optical sensors, magnetic sensors, electric field sensors for real time detection of objects and obstructions, global positioning system (GPS) sensors, inertial guidance means, encoder based feedback motors, laser guidance, reflective tapes, integrated image processing modules to navigate the SGV along a programmed path.

[0034] In the preferred embodiment of the present invention, the SGV is designed to accept a single command from a central master wirelessly and act on it by calculating the path from the source and destination based on the payload weight and subsequently assigning the transporters to pick up the material from a storage location (source location) and transferring them to the work facility or destination, while avoiding collision with other transporters and SGVs that may be encountered along the way within a industrial environment. A set of force torque sensors using strain gauges are incorporated into each of the transporters to measure weight of the payload before any task is performed. In most prior-art systems typically the SGVs and transporters are combined into one system to save cost and complexity and the cost of flexibility and scalability. In the present invention, each SGV is equipped only with the data processing task that enables multiple transporters to be utilised simultaneously making the whole system less complicated, inexpensive, increased reliability, scalable and adaptable to different types of applications.

[0035] In another embodiment of the present invention, multiple transporters may be utilised to move a payload with centre of gravity at a higher point, from a source location to the destination with a high probability of intersecting paths of other transporter pathways. The transporters in spite of not being connected physically, mechanically or electrically, are controlled through speed and acceleration proportional to the centre of gravity position, to ensure synchronised movement through close coordination between themselves and the SGV to avoid a safe free delivery of the payload. These synchronised and coordinated pathways are achieved through reinforced learning and machine learning techniques for a smooth and stable movement of the transporters irrespective of the size and weight payload, even when negotiating sharp turns or other complex intersections. Such a coordinated approach minimises the risk of the payload toppling over, thereby enhancing safety and efficiency in the transport process.

[0036] FIG. 1 shows an exemplary SGV system 100 according to the embodiment that is mounted on three rotary wheels 8a, 8b & 8c, driven by motor drivers integrated with guiding mechanisms to move in the X & Y direction. The SGV comprises guiding sensors 12a, 12b and 12c. a built in image-processing module integrated connected to a camera which is mounted with an omnidirectional mirror 15. enabling image capture of the surrounding area, to detect obstructions and travel along the programmed route. The images are also utilised for visual odometry and implementing solutions for simultaneous localization and mapping (SLAM) related issues. Due to its ability to capture images with a 360-degree view enabled by the omnidirectional mirror 15, better imaging data is available for optical flow, feature selection and matching. The combination of the panoramic image and the gyroscope feedback data allows a determination of an optimum movement path to produce a smooth and safe transfer of the payload from the source to the destination. An optical flow can comprise related techniques from image processing, control of navigation including motion detection, angular tilt, object segmentation, motion compensated encoding, and stereo disparity measurement.

[0037] With communication peripherals such as WiFi, Bluetooth and other forms of wireless modules, close monitoring and path guidance of the transporters is made possible by the SGV. Light indicators 10a, 10b and 10c are utilised to identify various functions and modes of the SGV operation. More details of the hardware features in the SGV will not be discussed as it is beyond the scope of the invention.

[0038] FIG. 2 shows the top view of the SGV system 100 in Fig 1. FIG. 3 shows the Side view of the SGV system 100 in Fig 2.

[0039] Fig.4 shows an isometric view of a transporter 20 consisting of Top lifting plate 25, a built in computer enclosed in a cabinet 30, a set of indicators 35 and built in communicating transmitters and receivers (not shown) located within the cabinet.

[0040] FIG. 5 shows the top view of the transporter 20 in Fig 4. The top plate 25 is fabricated with a non-slip surface to enable a stable platform for the payload to be lifted and carried around.

[0041] Fig. 6 shows the side view of the transporter 20 in Fig 4. The top plate 25 is retracted to the home position. Four wheels 45 ensure fast & accurate movement of the transporter. The wheels 45 are designed to move in multiple directions to enable smooth turns to prevent sharp angular shifts during payload transfer, with the help of an inbuilt Gyroscope.

[0042] In Fig.7 the top plate 25 is extended to lift the payload off the ground. A set of force torque sensors using strain gauges to measure weight of the payload is incorporated in every transporter to measure weight. Depending upon the pay load weight, size & its centre of gravity, multiple transporters operate in sync with: each other io ensure a stable movement. High-speed transfer is a key feature to maximise throughput, since the capacity of each transporter is a function of how efficiently it can travel from one point to another, based on die route assigned by the SGV that is determined by the obstructions and traffic at any point in time.

[0043] Fig 8 shows a typical manufacturing floor plan comprising a single SGV 100 (shown in Fig 1) managing a set of transporters 120, 130, 140 & 150. In the embodiment shown in Fig 8, SGV 100 controls the operation of all the transporters by communicating the source and destination along with the route path to move the raw material loaded on to a storage trolley. For eg: The transporters 120 and 130 are instructed to move trolley 200 loaded with raw materials to the workstation 300 for processing. The SGV 100 is also designed for multitasking by sending instructions in parallel or in sequence to transporters another set of transporters 140 and 150 for controlling speed, acceleration and angular stability to ensure safe movement of the payload 260 to workstation 320 for further processing. The SGV 100 is designed and programmed to process route paths / trajectories and utilisation of multiple transporters based on the pay load size & weight of the raw material to be transported, from a source location to its destination by understanding the dynamic positions of every other transporter encountered, to avoid collision. The payload characteristics are taken into account by the SGV 100 for determining the speed and acceleration of each transporter to maintain angular stability through the use of gyro sensors during moving, turning and stopping. This feature ensures safe, secure, and stable movement of material with the manufacturing floor resulting in higher productivity. The SGV and transporters are incorporated with high capacity Li-ion batteries capable of operating continuously for 6-8 hours with minimum charging intervals. Charging the batteries is facilitated by the SGV to ensure optimally charged transporters are always available for processing a payload at any given time by allocating charging intervals for each and every transporter with no impact on the operating efficiency. The SGVs also manage themselves by automatically moving towards charging stations during low activity periods to ensure no interruptions to the precess. The charging docks are not shown as they are out of the scope of this invention. The SG V 100 determines the number of transporters to be deployed to move a particular payload based on the character (Size. Weight & Centre of Gravity) of the payload. They also control the transporters 120,130,140& 150 to operate efficiently in narrow aisles with low error tolerance by utilising control techniques, fuzzy logic, neural networks, combined with control theory. The SGV 100 comprise algorithms with position control strategies for transporters 120,130,140& 150, that take into account power-torque-payload relationships, the wireless sensors and guidance system used and the braking system employed (for eg: negative G-force technology) to stop safely and accurately.

[0044] At any point in time, the SGV 100 maintains a full view of the industrial floor through precise monitoring of all transporters, trolleys and any other obstacles through a technique called SLAM (Simultaneous Localization and Mapping) by employing sensors and vision-based systems with a 360 degree view of the working environment. SLAM helps SGVs navigate the manufacturing floor effectively and safely. The SGV 100 assigns tasks to the transporters based on priority, availability, and efficiency with utmost care to ensure a safe and efficient passage of the payload to its destination. By separating the operating administration between the SGV and the transporters, the overall raw material transfer system is more efficient and scalable. Multiple SGVs and transporters can be deployed as they are all interlinked in terms of the operating environment and payload processing distribution. The probability of intrusions and path mapping is completely eliminated due to the central mode of the system architecture allotted to one main master SGV. The SGV is programmed with scheduling algorithms that balance workload, minimise waiting times, and optimise overall system performance through real time computing of transporter movement paths, number of transporters to be deployed for a given payload weight, angular paths to avoid tilts at any given speed, while taking into account any obstructions that may occur during transportation. The SGV continuously adjusts their instructions and commands to the transporters based on sensor and vision system feedback in conjunction with PID (Proportional-Integral-Derivative) controllers commonly used for closed loop control of speed, angular trajectories and current position, and simultaneously avoiding resonant modes that cause vibrations in transporters. For the purpose of understanding a slightly complex industrial working environment Fig 8 shows two other storage trolleys 220 and 240 that may be situated at a different location 105. It is evident that more than one SGV may be deployed along with multiple transporters if the manufacturing environment requires such an implementation where more workstations may be incorporated. In such cases, Dynamic path planning algorithms are utilised wherein the SGVs adapt to the changing environment based on real time sensor data & obstructions. Model Predictive Control MPC is implemented in the control software that has the ability to anticipate future events and can take appropriate actions accordingly, minimising stoppages when unusual situations are encountered. SGV utilises built in Al tools combined with machine learning models incorporated with reinforced learning tools to achieve optimal trajectory paths for speedy and efficient movement of the payload. Reinforced learning tools fine-tune intelligent operating models based on historical data to improve path predictions resulting in optimum use of industrial space.

[0045] SGVs are incorporated with cyber security models in the software application, to flag any intrusions and unauthorised access to sensitive information that may include but not limited to process parameters, raw materials used and throughput data.

[0046] The SGVs functionality is intentionally localised in terms of the operations with minimum intervention from an external command centre, thus reducing the risks from cyber security threats and intrusions. In the event of a threat, the risk is minimised due to the fact that the control and planning systems are separate and localised.

[0047] Traditional SGVs suffer from lack of judgement during the decision making process as they usually operate based on pre-programmed rules and algorithms due to which they are not adaptable in novel situations. Traditional SGVs performing both planning and control suffer from slow and compromised responses in dynamic conditions. The present invention differs from conventional systems by isolating the control and planning aspects between the transporter and SGV respectively.

Claims

Claims:

1. A localised payload moving system comprising:a smart guided vehicle (SGV), comprising:a multidirectional motorised module that behaves as a guiding system with ability to to move in any direction;at least one omnidirectional camera to capture images for a 360 view;a vision system to process images and detect objects around it for the control system to determine the pathways for the transporters;communicating electronics such as WiFi & Bluetooth for sending and receiving data;sensors to detect nearby objects and obstructions in real time in combination with thermal sensors, lasers, radars & movement detectors;a high capacity Li-ion battery capable of operating continuously for long periods of time with minimum charging intervals;at least a pair of transporters comprising:communicating electronics such as Wifi, Bluetooth for sending and receiving data;sensors to detect nearby objects and obstructions in real time in combination with thermal sensors, lasers, radars, movement detectors and gyro sensors; a set of force torque sensors using strain gauges to measure weight of the payload;proportional integral derivative (PID) controllers for closed loop control of speed and position and angular trajectories to avoid resonant modes in transporters;a platform mounted on the top for lifting the payload and mechanically integrated with a lifting mechanism;a set of weighing gauges to measure the weight of the payload and communicate the data to the SGV;a high capacity Li-ion battery capable of operating continuously for long periods of time with minimum charging intervals.

2. The system of claim 1, wherein the SGV determines if more than one transporter is required and invoking their services, based on the readings received from the transporter’ s weighing gauges.

3. The system of claim 1, farther comprising a dedicated network of transporters working within a dedicated area to minimise long distance movement of payloads resulting in increased efficiency and speed.

4. The system of claim 1, further comprising a second SGV to assist in the management of path planning for some transporters to enable the first transporter to perform other tasks, if such a situation occurs.

5. A localised payload moving method comprising:the smart guided vehicle receiving a command from a central master wirelessly and calculating the path from the source and destination based on the payload weight; utilising built in Al tools combined with machine learning models and incorporated with reinforced learning tools to achieve optimal trajectory paths for speedy and efficient mo vement of the pay load;reinforced learning tools that fine tune intelligent operating models based on historical data to improve path predictions resulting in optimum use of industrial space;creating a virtual view of the operating environment through a technique called SLAM (Simultaneous Localization and Mapping) by employing sensors and vision based systems with a 360 degree view of the working environment;Model Predictive Control MPC with the ability to anticipate future events and take control actions accordingly to avoid collisions and stoppages when unusual situations are encountered;ability to multitask in the form of sending instructions in parallel or in sequence to multiple transporters to control their speed, acceleration and angular stability for safe movement of the payload;capability to manage charging periods of the transporter Lithium ion batteries by the SGV, to ensure optimally charged transporters at any given time.

6. The method of claim 5, further comprising a charged SGV which manages itself to ensure no interruptions to the process;7. The method of claim 5, further comprising the step of utilising dynamic path planning algorithms implemented within the SGV to adapt to the changing environment based on real time sensor data & obstructions.

8. The method of claim 5, further comprising a localised functionality for the SGV in terms of the operations with minimum intervention from an external command centre, resulting in no risk from cyber security threats and intrusions.

9. The method of claim 5, further comprising the SGV incorporated with cyber security models to flag any intrusions and unauthorised access to sensitive information that may include but not limited to process parameters, raw materials used and throughput data.

10. The method of claim 5, further comprising a feature whereby the SGV continuously adjusts their instructions and commands to the transporters based on sensor and vision system feedback in conjunction with PID (Proportional-Integral-Derivative) controllers commonly used for closed loop control of speed, angular trajectories, current position and simultaneously avoiding resonant modes that cause vibrations in transporters.

11. The method of claim 5, further comprising a feed forward control method that utilises sensors to detect disturbances such as objects and obstructions in real time that affect the transporter movements and apply a feedback control input to minimise the effect of resonant modes that may cause vibration & instability.

12. The method of claim 5, further comprises a process that ensures a dedicated network of transporters working within a dedicated area resulting in simpler logistics management of transporters in terms of speed and efficiency.

13. The method of claim 5 further comprising an action of invoking a second SGV to take over the management of path planning for the transporters to free up the first SGV to perform other tasks, if such a situation occurs.

14. The method of claim 5, further comprising of determining the number of transporters required to move a payload and invoking their services respectively.

15. The method of claim 13, further comprising the action of relaying signals through multiple communication wireless channels such as Bluetooth, Wifi and 4G.

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