Lidar systems for vehicles with multiplexed point clouds

Abstract

An exemplary light-based detection and distance measurement (lidar) system for a vehicle comprises at least one transmitter configured to send lidar signals at multiple frequencies, an omnidirectional emitting lidar configured to send signals via the at least one transmitter, and multiple receivers configured to receive lidar signals reflected from the environment surrounding the vehicle. Each of the multiple receivers is configured to receive reflected lidar signals at a different frequency.A vehicle control module is configured to combine frequency data from reflected lidar signals received at the multiple receivers into a point cloud array, generate a multiplexed point cloud according to the point cloud array, provide the multiplexed point cloud to a perception stack configured to process three-dimensional images, and automatically control steering, acceleration, and braking of the vehicle according to the multiplexed point cloud provided to the perception stack.

Description

Introduction

[0001] The information provided in this section serves the purpose of presenting the general context of the disclosure. The work of the inventors mentioned herein, insofar as it is described in this section, as well as aspects of the description that cannot be classified as prior art at the time of filing, are neither expressly nor implicitly recognized as prior art with respect to the present disclosure.

[0002] The present disclosure relates to lidar systems for vehicles, including systems that use multiplexed point clouds.

[0003] Some vehicles use lidar systems to create images of their surroundings for automated vehicle control, such as autonomous driving. Lidar systems determine distances by aiming a laser at an object or surface and measuring the time it takes for the reflected light to return to the receiver. Summary

[0004] An exemplary light detection and ranging (Lidar) system for a vehicle comprises at least one transmitter configured to send Lidar signals at multiple frequencies, wherein the at least one transmitter is coupled to the vehicle; an omnidirectional emitting Lidar configured to send signals via the at least one transmitter; multiple receivers configured to receive Lidar signals reflected from an environment around the vehicle, each of the multiple receivers configured to receive reflected Lidar signals at a different frequency; and a vehicle control module configured to combine frequency data from reflected Lidar signals received at the multiple receivers into a point cloud array, generating a multiplexed point cloud according to the point cloud array.The multiplexed point cloud is provided to a perception stack configured to process three-dimensional images, and the system automatically controls the steering, acceleration, and braking of the vehicle according to the multiplexed point cloud provided to the perception stack.

[0005] In some examples, each of the multiple receivers is coupled to the vehicle at a different location. In some examples, the vehicle control module is configured to index a frequency and sweep angle for lidar signals received by each of the multiple receivers.

[0006] In some examples, the vehicle control module is configured to embed the indexed frequency and scan angle into a point cloud. In other examples, the vehicle control module is configured to create an array containing point cloud scan angles based on an index of the point cloud's scan angle, and iterate through these scan angles to combine the frequency data into the point cloud array.

[0007] In some examples, the vehicle control module is configured to detect at least one object in the point cloud array, index at least one object across multiple scanning angles of the point cloud array, and track the position of the object across the multiple scanning angles of the point cloud array.

[0008] In some examples, the vehicle control module is configured to measure the point density of the point cloud array at a current index and compare the point density to a specified point density threshold.

[0009] In some examples, the vehicle control module is configured to provide the multiplexed point cloud to the perception stack in response to the point density being greater than the specified point density threshold.

[0010] In some examples, the vehicle control module is configured to detect a next sampling angle in the point cloud array in response to the point density being less than the specified point density threshold, and to update the multiplexed point cloud according to the next sampling angle in the point cloud array.

[0011] In some examples, updating the multiplexed point cloud includes removing duplicate objects from the multiplexed point cloud. In other examples, updating the multiplexed point cloud includes normalizing the point density using a defined consistent resolution and deleting duplicate points in the multiplexed point cloud as a result of the point cloud multiplexing.

[0012] In some examples, the vehicle control module is configured to track an object's position within the multiplexed point cloud to determine a final object target. In some examples, the multiplexed point cloud contains no blind spots with a point density below a specified point density threshold.

[0013] An exemplary method for operating a light-based detection and distance measurement (Lidar) system for a vehicle comprises transmitting, via at least one Lidar transmitter, lidar signals at multiple frequencies, wherein the at least one Lidar transmitter is coupled to the vehicle and a parabolic reflector is positioned to reflect the lidar signals transmitted by the at least one Lidar transmitter; receiving, via multiple Lidar receivers, lidar signals reflected from an environment around the vehicle, each of the multiple Lidar receivers receiving reflected lidar signals at a different frequency; combining frequency data of reflected Lidar signals received at the multiple Lidar receivers into a point cloud array; generating a multiplexed point cloud according to the point cloud array; and providing the multiplexed point cloud to a perception stack configured to…that it processes three-dimensional images, and automatically controls the steering, acceleration, and braking of the vehicle according to the multiplexed point cloud provided to the perception stack.

[0014] In some examples, each of the multiple lidar receivers is coupled to the vehicle at a different location. In some examples, the method involves indexing a frequency and scanning angle for reflected lidar signals received by each of the multiple lidar receivers.

[0015] In some examples, the method involves embedding the indexed frequency and scan angle into a point cloud. In other examples, the method involves generating an array containing point cloud scan angles based on an indexing of the point cloud scan angle and iterating through the point cloud scan angles to combine the frequency data into the point cloud array.

[0016] In some examples, the method includes detecting at least one object in the point cloud array, indexing the at least one object across multiple scanning angles of the point cloud array, and tracking the position of the object across the multiple scanning angles of the point cloud array.

[0017] An exemplary light-based detection and distance measurement (Lidar) system for a vehicle comprises at least one transmitter configured to send lidar signals at multiple frequencies, wherein the at least one transmitter is coupled to the vehicle; multiple receivers configured to receive lidar signals reflected from an environment around the vehicle, each of the multiple receivers being configured to receive reflected lidar signals at a different frequency; and a vehicle control module configured to combine frequency data from reflected lidar signals received at the multiple receivers into a point cloud array, generate a multiplexed point cloud according to the point cloud array, provide the multiplexed point cloud to a perception stack configured to process three-dimensional images, and a steering system.automatically controls the acceleration and braking of the vehicle according to the multiplexed point cloud provided to the perception stack.

[0018] Further applications of the present disclosure will become apparent from the detailed description, the claims, and the drawings. The detailed description and the specific examples serve only for illustration and are not intended to limit the scope of the disclosure. Brief description of the drawings

[0019] The present revelation is more fully understood from the detailed description and the accompanying drawings. Fig. Figure 1 is a functional block diagram of an exemplary vehicle containing a lidar system with multiple lidar receivers, according to an example in the present disclosure. Fig. Figure 2 is an exemplary block diagram of a multi-frequency lidar transmission system for a vehicle containing multiple lidar receivers, according to an example in the present disclosure. Fig. Figure 3 is a flowchart of an exemplary process for controlling a lidar system for a vehicle with multiple lidar receivers according to an example in the present disclosure. Fig. Figure 4 is a flowchart of an exemplary process for acquiring point cloud frequency information based on received signals in the process of Fig. 3 according to an example from the present revelation. Fig. Figure 5 is a flowchart of an exemplary process for generating multiplexed point clouds in the process of Fig. 3 according to an example from the present revelation.

[0020] Reference numerals can be reused in the drawings to identify similar and / or identical elements. Detailed description

[0021] In some embodiments, a vehicle light-based detection and distance measurement (lidar) system may include a multi-frequency lidar transmitter and multiple lidar receivers configured to receive reflected lidar signals at different frequencies. Some lidar technologies reach their limits in generating a complete and gapless point cloud due to the presence of objects. In some exemplary embodiments described herein, a lidar system using a multiplexed point cloud may optimize and remove these shadows (e.g., blind spots where no point cloud data is obtained or where the point density is not high enough to detect objects).

[0022] For example, the use of multiplexing point clouds across multiple frequencies can be achieved using a single lidar system or a single lidar transmitter with multiple receiver modules. The lidar system can capture data from different frequencies and angles, providing a more comprehensive and accurate representation of the vehicle's surroundings.

[0023] Exemplary point cloud multiplexing techniques described herein can enable a lidar system to collect data from different perspectives, thereby reducing or minimizing the impact of shadows and gaps in the point cloud data caused by objects. By effectively combining information from point clouds using multiple frequencies and utilizing multiple lidar receiver modules, the resulting multiplexed point cloud can provide a more complete and detailed representation of the vehicle's surroundings.

[0024] In some examples, a vehicle's lidar system architecture incorporates multiple wavelengths and uses multiplexing techniques to reduce or eliminate object shadows, resulting in a point cloud with few or no blind spots. This can be achieved by separating the lidar transmit and receive functions into a dedicated transmitting unit and multiple receivers located elsewhere on the vehicle. This approach can facilitate the generation of a coherent, complete three-dimensional (3D) image from the point cloud data.

[0025] Now on Fig. Referring to 1, a vehicle comprises 10 wheels 12 and 13, which can switch between front and rear wheels depending on the direction of movement of the vehicle 10 (e.g., driverless vehicles may not have a defined front). In Fig. 1 A drive unit 14 selectively transmits torque to the wheels 12 and 13, respectively, via drive trains 16 and 18. The vehicle 10 can include various types of drive units. For example, the vehicle can be an electric vehicle such as a battery electric vehicle (BEV), a hybrid vehicle, a fuel cell vehicle, an internal combustion engine vehicle (ICE), or another type of vehicle.

[0026] Some examples of the drive unit 14 can include any suitable electric motor, a power inverter, and a motor controller configured to control circuit breakers within the power inverter to adjust the motor speed and torque during drive and / or regeneration. During drive or regeneration, a battery system supplies power to or receives power from the electric motor of the drive unit 14 via the power inverter.

[0027] While the vehicle 10 in Fig. While vehicle 10 comprises a drive unit 14, it can also have other configurations. For example, two separate drive units can power wheels 12 and 13, one or more individual drive units can power individual wheels, etc. As can be imagined, other vehicle configurations and / or drive units can be used.

[0028] The vehicle control module 20 can be configured to control the operation of one or more vehicle components, such as the drive unit 14 (e.g., by issuing commands regarding torque settings of an electric motor in the drive unit 14). The vehicle control module 20 can receive inputs for controlling vehicle components, such as signals received from a steering wheel, accelerator pedal, etc. For safety reasons, the vehicle control module 20 can monitor the vehicle's telematics, such as vehicle speed, vehicle location, braking, and acceleration.

[0029] The vehicle control module 20 can receive signals from any suitable components to monitor one or more aspects of the vehicle, including one or more vehicle sensors (such as cameras, lidar transmitters and receivers, microphones, pressure sensors, wheel position sensors, positioning sensors such as global positioning system (GPS) antennas, etc.). Some sensors can be configured to monitor the vehicle's current movement, acceleration, steering wheel position, etc.

[0030] As in Fig. As shown in Figure 1, the vehicle 10 comprises a lidar system 22, which includes a multi-frequency transmitter 24 and a parabolic reflector 26. The multi-frequency transmitter can be configured to send lidar signals at multiple frequencies to determine distances, for example, by targeting objects or surfaces around the vehicle with a laser and measuring the time it takes for the reflected light to return to a receiver. Examples of frequencies include, but are not limited to, 10 Hz, 100 Hz, signals with nm wavelengths, etc. The multi-frequency transmitter 24 can be configured to change the sweep or scan angles for different signals or different signal frequencies.

[0031] The vehicle 10 comprises a first lidar receiver 28 and a second lidar receiver 30, each configured to receive reflected lidar signals transmitted by the multi-frequency transmitter 24 and reflected by objects or surfaces in an environment surrounding the vehicle. In some examples, each lidar receiver can be configured to receive a different frequency of reflected lidar signals and can be positioned at different locations on the vehicle 10 (e.g., the lidar receivers can be decoupled from the multi-frequency transmitter 24). The vehicle control module 20 can store a position and / or distance of each lidar receiver relative to the multi-frequency transmitter 24 in order to triangulate the reflected signals received by each lidar receiver. The lidar signals can be transmitted in fixed directions or can scan in multiple directions around the vehicle 10.

[0032] An optional parabolic reflector 26 can reflect signals transmitted by the multi-frequency transmitter 24 to increase the number of angles or the range of the signals, thus providing greater coverage of an area around the vehicle 10. The parabolic reflector 26 can have any suitable shape for dispersing the reflection of the transmitted signals, such as a donut-shaped mirror, a parabolic sphere, an inverted mushroom to provide 360-degree visibility, etc. The parabolic reflector 26 can cover other sensors beneath it. Although in Fig. Figure 1 shows a lidar transmitter and two lidar receivers; other exemplary embodiments may include more transmitters and / or receivers. In some embodiments, an omnidirectionally emitting lidar may be configured to transmit signals via at least one transmitter.

[0033] In some examples, the reflected lidar signals received by the first lidar receiver 28 and a second lidar receiver 30 can be combined into a multiplexed point cloud for 3D imaging control of vehicle functions such as automated driving. For example, multiplexed point cloud data based on lidar signals received by the lidar receivers can be provided to a perception stack that automatically controls the steering, acceleration, and braking of the vehicle 10 to provide an autonomous advanced driver assistance system (ADAS).

[0034] The vehicle control module 20 can communicate with another device via a wireless communication interface, which may include one or more wireless antennas for transmitting and / or receiving wireless communication signals. For example, the wireless communication interface can communicate via any suitable wireless communication protocol, including but not limited to vehicle-to-everything (V2X) communication, Wi-Fi communication, wireless area network (WAN) communication, cellular communication, personal area network (PAN) communication, short-range or near-field communication (e.g., Bluetooth), etc.The wireless communication interface can communicate with a remote computing device via one or more wireless and / or wired networks. With regard to vehicle-to-everything (V2X) communication, the vehicle can include one or more V2X transceivers (e.g., V2X signal transmitting and / or receiving antennas).

[0035] In some cases, the lidar system can mask shadows cast by objects in the lidar point cloud (due to multiplexing point cloud data from different frequencies or scanning angles), resulting in a point cloud without dead zones. The lidar system can capture data from all angles and perspectives to provide a more comprehensive and accurate representation of the environment.

[0036] Integrating multiple lidar receivers into the lidar system extends the detection range. For example, the lidar system can detect objects that are farther away, improving its overall performance and capabilities. Using multiple lidar receivers can improve the probability of detection (PoD) of objects around the vehicle. With more lidar receivers collecting data, the lidar system can achieve a higher degree of accuracy in detecting and identifying objects in its environment.

[0037] In some examples, point cloud data can be converted into an accurate image more quickly, while also increasing the image resolution. The lidar system can process and analyze the data more efficiently, resulting in a clearer and more detailed representation of the environment.

[0038] Exemplary lidar systems can generate a 360-degree image using a single, non-rotating lidar sensor. This can reduce or eliminate the need for multiple sensors to cover an entire field of view, simplifying the design and lowering costs. Integrating multiple receivers can reduce the size of the lidar housing. The lidar system can be more compact and lighter, simplifying its integration into various applications and platforms.

[0039] In some cases, improved lidar systems can reduce or eliminate the need for a heat sink, as the computational and power requirements of the lidar system can be lower due to the use of a single module. This can reduce the complexity and cost of the system while also improving its overall efficiency. Exemplary lidar systems can also address the problem of signal attenuation, ensuring that the lidar system maintains a strong and reliable signal throughout its operation. This can enable the lidar system to accurately capture and analyze data without loss or degradation of quality.

[0040] Now on Fig. 2. Referring to point 2, a Lidar System 200 can be a multi-frequency Lidar transmission system with multiple receivers. The Lidar System 200 from Fig. 2 can add to the lidar system 22 of Fig. 1 including the first lidar receiver 28 and the second lidar receiver 30.

[0041] As in Fig. As shown in Figure 2, a multi-frequency lidar transmitter sends 204 lidar signals at several frequencies, such as a first frequency of 208, a second frequency of 212, and a third frequency of 216. Although Fig. 2. Three frequencies of lidar signals are illustrated; other examples may include more or fewer frequencies.

[0042] Signals of different frequencies can be reflected by an optional 220 parabolic reflector to increase the signal coverage area around the vehicle. The transmitted signals are then received by multiple lidar receivers after being reflected by objects or surfaces in the environment surrounding the vehicle. Fig. Figure 2 illustrates a first lidar receiver 224, a second lidar receiver 228 and a third lidar receiver 232, each of which can be configured to receive reflected signals at a corresponding frequency of the first frequency 208, the second frequency 212 and the third frequency 216.

[0043] Other exemplary embodiments may include more or fewer lidar receivers. As explained below, the signals received by each of the first lidar receiver 224, the second lidar receiver 228, and the third lidar receiver 232 can be converted into point cloud information, which includes indexing the frequency and the scanning angle according to the received signals to generate a multiplexed point cloud.

[0044] Fig. Figure 3 is a flowchart of an example process for controlling a lidar system for a vehicle with multiple lidar receivers. The process of Fig. 3 can be done, for example, using the vehicle control module 20 of Fig. 1 can be implemented. At 304, the process begins by sending lidar signals at multiple frequencies. For example, the multi-frequency transmitter 24 can be used. Fig. 1. It should be configured to send lidar signals at various predefined frequency values.

[0045] The vehicle control module is configured to reflect the transmitted lidar signals at 308 using a parabolic reflector. For example, the signals from the multi-frequency transmitter 24 can be reflected. Fig. 1 transmitted multi-frequency lidar signals from parabolic reflector 26 of Fig. 1 are reflected to scatter the lidar signals over a wider area or angular range around the vehicle.

[0046] The vehicle control module is configured to receive lidar signals reflected from the surrounding environment at 312 on multiple decoupled lidar receivers on the vehicle. For example, the first lidar receiver can receive 28 and the second lidar receiver 30 from Fig. 1 Lidar signals at different frequencies were received after the lidar signals sent by the multi-frequency transmitter 24 and the parabolic reflector 26 were reflected by objects in an environment around the vehicle 10.

[0047] The vehicle control module is configured to acquire 316 point cloud frequency information based on the received lidar signals. Further details regarding the acquisition of point cloud frequency information are provided below with reference to Fig. 4 discussed.

[0048] The vehicle control module is configured to generate a multiplexed point cloud at 320° that cannot contain any blind spots (e.g., areas in 3D images of the multiplexed point cloud where there is insufficient point cloud data or insufficient point density to determine whether objects are present). Further details regarding the generation of the multiplexed point cloud are provided below with reference to... Fig. 5 discussed.

[0049] The vehicle control module is configured to provide three-dimensional images to a vehicle perception and viewing stack based on the multiplexed point cloud at 324. For example, the vehicle control module can be configured to generate one or more 3D images from the multiplexed point cloud for use by one or more vision control algorithms of the vehicle.

[0050] The vehicle control module is configured to automatically control steering, acceleration, and braking of the vehicle based on 3D imaging at 328. For example, the multiplexed point cloud without blind spots can be used by an advanced driver assistance system (ADAS) to control the vehicle for automated driving.

[0051] Fig. Figure 4 is a flowchart of an exemplary process for acquiring point cloud frequency information based on received signals in the process of Fig. 3. The process of Fig. 4 can be done, for example, using the vehicle control module 20 of Fig. 1. At 404, the process begins by indexing the frequency and scan angle for lidar signals received by multiple vehicle lidar receivers. For example, the vehicle control module can index frequency and scan angle values ​​that reflect the signal received by the first lidar receiver 28 and the second lidar receiver 30. Fig. 1 received lidar signals correspond to.

[0052] The vehicle control module is configured to embed the frequency and sampling angle data into a point cloud at event 408. The vehicle control module then generates an array containing the point cloud sampling angles at event 412.

[0053] The vehicle control module is configured to select a first scan angle from 1 to N at 416. For example, the array may contain point cloud scan angles indexed from 1 to N according to different lidar receivers, and the vehicle control module may be configured to iterate through each of the point cloud scan angle values.

[0054] The vehicle control module is configured to combine 420 frequency data points into a point cloud array. For example, the frequency data can correspond to different lidar signal frequencies received by different lidar receivers, each tuned to a different frequency and mounted in various positions on the vehicle.

[0055] The vehicle control module is configured to determine at 424 whether a final scanning angle in the array has been reached. For example, in an array of 1 to N scanning angles, the control unit can determine whether the Nth scanning angle has been processed.

[0056] If not, the controller proceeds to 428 to select the next sampling angle in the array, and then at 420 combines the frequency data into the point cloud array based on the next selected sampling angle. If the last sampling angle in the array is reached at 424, the controller proceeds to 432 to save the point cloud array, including the combined frequency data from each sampling angle.

[0057] Fig. Figure 5 is a flowchart of an exemplary process for generating multiplexed point clouds in the process of Fig. 3. The process of Fig. 5 can be done, for example, using the vehicle control module 20 of Fig.1. At 504, the process begins by performing object detection on a point cloud containing frequency information. For example, one or more automated object detection algorithms for lidar point cloud image processing can be used to detect objects in the environment around the vehicle.

[0058] The vehicle control module is configured to perform object indexing on 508. For example, each object detected in the point cloud can be assigned an index value to track the object across different point cloud frequency segments or scanning angles.

[0059] The vehicle control module is configured to track an object's position based on object detection and indexing at 512. For example, the controller can track the position of a specific detected object across different point cloud frequency segments or scanning angles using an index assigned to that specific detected object.

[0060] The vehicle control module is configured to measure point density at a current index on page 516. For example, the vehicle control module can select an initial scanning angle index for the point cloud and measure the point density at that scanning angle index. The point density can be measured using any suitable algorithm and can indicate the density of points across the entire point cloud, the density of points at specific locations within the point cloud, the density of points in different sections of the point cloud, and so on. The point density can indicate whether there are any blind spots in the point cloud, where there is insufficient data to determine the presence or absence of objects at that location.

[0061] For example, the vehicle control module is configured to determine at 520 whether the measured point density is less than a defined point density threshold, which can be calibrated. The point density threshold can be set as a threshold that indicates whether there are any blind spots in the point cloud, where there is insufficient point data to determine the presence or absence of objects at that location.

[0062] If the measured point density at 524 is below the threshold, the controller proceeds to 532 to acquire the next scan angle and begin multiplexing the point cloud. For example, the controller can acquire point cloud data from a different scan angle, which may correspond to one or more different frequencies of reflected lidar signals received by one of several lidar receivers. The controller can then multiplex point cloud data according to the selected scan angle with point cloud data processed for previous scan angles.

[0063] The vehicle control module is configured to remove object duplications from the multiplexed point cloud at 536. For example, if an object identified in a current point cloud scan angle index is a duplicate of the same object identified in a previous point cloud scan angle index, the control unit can remove the duplicate object data so that the same object is identified only once in the multiplexed point cloud.

[0064] The vehicle control module is configured to normalize the point density at 540 using a consistent resolution in the multiplexed point cloud. For example, the controller can delete duplicate points resulting from multiplexing point cloud data from different scanning angle indices, thus maintaining a consistent point resolution while adding additional point cloud data from different scanning angle indices.

[0065] The vehicle control module is configured to re-track at 544 object positions in the multiplexed point cloud to determine a final object target. For example, the control unit can use an object index to update or confirm an object's position in the multiplexed point cloud after additional data from a different scan angle index has been added to the multiplexed point cloud.

[0066] The controller then returns to 516 to measure a point density at index 524 after updating the multiplexed point cloud. Once the measured point density at 524 exceeds the defined point density threshold, the vehicle control module is configured to send the multiplexed point cloud to a perception stack (e.g., for use in an automated driving controller or other vehicle vision systems). Due to the multiplexing of the point cloud data, which covers any blind spots that might occur in any single sampling angle index of the point cloud data, the multiplexed point cloud cannot contain any blind spots.

[0067] The preceding description is merely illustrative and intended to limit the scope of the revelation, its application, or uses. The comprehensive doctrine of revelation can be implemented in a multitude of forms. Therefore, although this revelation contains particular examples, the true scope of the revelation should not be so limited, since other modifications will become apparent upon study of the drawings, the description, and the following claims. It should be understood that one or more steps within a process may be carried out in a different order (or simultaneously) without altering the principles of the present revelation.Furthermore, although each of the embodiments described above is characterized by certain features, one or more of these features described in relation to any embodiment of the disclosure may be implemented in one of the other embodiments and / or combined with features of one of the other embodiments, even if this combination is not expressly described. In other words, the described embodiments are not mutually exclusive, and permutations of one or more embodiments with each other remain within the scope of this disclosure.

[0068] Spatial and functional relationships between elements (for example, between modules, circuit elements, semiconductor layers, etc.) are described using various terms, including "connected," "interlocked," "coupled," "adjacent," "near or beside," "on," "above," "below," and "arranged." Unless explicitly described as "direct," when a relationship between first and second elements is described in the above disclosure, this relationship may be a direct relationship, in which no other intervening elements exist between the first and second elements, or it may be an indirect relationship, in which one or more intervening elements (either spatial or functional) exist between the first and second elements.As used here, the phrase “at least one of A, B and C” should be understood as meaning a logical (A OR B OR C) using a non-exclusive logical OR, and should not be understood as meaning “at least one of A, at least one of B and at least one of C”.

[0069] In the diagrams, the direction of an arrow, as indicated by its tip, generally illustrates the flow of information (e.g., data or instructions) that is relevant to the illustration. For example, if Element A and Element B exchange a variety of information, but information transferred from Element A to Element B is important for the illustration, the arrow may point from Element A to Element B. This unidirectional arrow does not imply that no other information is transferred from Element B to Element A. Furthermore, Element B may send requests for, or acknowledgments of, information to Element A in connection with the information transferred from Element A to Element B.

[0070] In this application, including the definitions below, the term "module" or the term "controller" may be replaced by the term "circuit". The term "module" may refer to, be part of, or include an application-specific integrated circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combinational logic circuit; a field-programmable gate array (FPGA); a processor circuit (shared, dedicated, or group) that executes code; a memory circuit (shared, dedicated, or group) that stores code executed by the processor circuit; other suitable hardware components that provide the described functionality; or a combination of some or all of the above components, such as in a system-on-a-chip.

[0071] The module may contain one or more interface circuits. In some examples, the interface circuits may include wired or wireless interfaces connected to a local area network (LAN), the internet, a wide area network (WAN), or combinations thereof. The functionality of any given module of this disclosure may be distributed among multiple modules connected via interface circuits. For example, multiple modules may enable load balancing. In another example, a server module (also known as a remote or cloud module) may perform some functions for a client module.

[0072] The term "code," as used above, can include software, firmware, and / or microcode, and can refer to programs, routines, functions, classes, data structures, and / or objects. The term "shared processor circuit" refers to a single processor circuit that executes some or all of the code from multiple modules. The term "group processor circuit" refers to a processor circuit that, in combination with additional processor circuits, executes some or all of the code from one or more modules. References to multiple processor circuits include multiple processor circuits on separate chips, multiple processor circuits on a single chip, multiple cores of a single processor circuit, multiple threads of a single processor circuit, or a combination of the above.The term shared memory circuit refers to a single memory circuit that stores some or all of the code from multiple modules. The term group memory circuit refers to a memory circuit that, in combination with additional memory, stores some or all of the code from one or more modules.

[0073] The term storage circuit is a subset of the term computer-readable medium. The term computer-readable medium, as used here, does not include transitory electrical or electromagnetic signals that propagate through a medium (such as on a carrier wave); the term computer-readable medium can therefore be considered material and non-transient.Non-restrictive examples of a non-transient, physical, computer-readable medium include non-volatile memory circuits (such as a flash memory circuit, a erasable programmable read-only memory circuit, or a mask read-only memory circuit), volatile memory circuits (such as a static random access memory circuit or a dynamic random access memory circuit), magnetic storage media (such as an analog or digital magnetic tape or a hard disk drive), and optical storage media (such as a CD, a DVD, or a Blu-ray Disc).

[0074] The devices and methods described in this application can be partially or fully implemented by means of a special-purpose computer created by configuring a general-purpose computer to perform one or more specific functions embodied in computer programs. The functional blocks, flowchart components, and other elements described above serve as software specifications that can be translated into computer programs through the routine work of a person skilled in the art or a programmer.

[0075] Computer programs contain instructions executable by processors, stored on at least one non-transient, physical, computer-readable medium. Computer programs may also contain or rely on stored data. Computer programs may include a basic input / output system (BIOS) that interacts with the computer's special-purpose hardware, device drivers that interact with specific devices of the computer for special purposes, one or more operating systems, user applications, background services, background applications, etc.

[0076] The computer programs can contain: (i) descriptive text to be parsed, such as HTML (Hypertext Markup Language), XML (Extensible Markup Language), or JSON (JavaScript Object Notation); (ii) assembly code; (iii) object code generated from source code by a compiler; (iv) source code for execution by an interpreter; (v) source code for compilation and execution by a just-in-time compiler; etc. For example, source code can be written using syntax from languages ​​such as C, C++, C#, Objective-C, Swift, Haskell, Go, SQL, R, Lisp, Java®, Fortran, Perl, Pascal, Curl, OCaml, Javascript®, HTML5 (Hypertext Markup Language 5th Revision), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Flash®, and Visual Basic®. Include Lua, MATLAB, SIMULINK and Python®. legend

[0077] In the drawing figures, N stands for no and Y for yes.

Claims

[1] Light-based detection and distance measurement (Lidar) system for a vehicle, wherein the Lidar system comprises: at least one transmitter configured to send lidar signals at multiple frequencies, wherein the at least one transmitter is coupled to the vehicle; an omnidirectional emitting lidar configured to transmit signals via at least one transmitter; multiple receivers configured to receive lidar signals reflected from an environment around the vehicle, each of the multiple receivers configured to receive reflected lidar signals at a different frequency; and a vehicle control module that is configured to: Frequency data from reflected lidar signals received at multiple receivers are combined into a point cloud array; a multiplexed point cloud is generated according to the point cloud array; the multiplexed point cloud is provided to a perception stack configured to process three-dimensional images; and automatically controls the steering, acceleration, and braking of the vehicle according to the multiplexed point cloud provided to the perception stack. [2] Lidar system according to claim 1, wherein each of the multiple receivers is coupled to the vehicle at a different location on the vehicle. [3] Lidar system according to claim 1, wherein the vehicle control module is configured to index a frequency and scanning angle for reflected lidar signals received by each of the multiple receivers. [4] Lidar system according to claim 3, wherein the vehicle control module is configured to embed the indexed frequency and the indexed scanning angle into a point cloud. [5] Lidar system according to claim 4, wherein the vehicle control module is configured such that it: Based on an indexing of the point cloud's sampling angle, an array containing point cloud sampling angles is generated; and The process is iterated through the point cloud sampling angles to combine the frequency data into the point cloud array. [6] Lidar system according to claim 1, wherein the vehicle control module is configured such that it: at least one object is detected in the point cloud array; at least one object is indexed across multiple scanning angles of the point cloud array; and The position of the object is tracked across the multiple scanning angles of the point cloud array. [7] Lidar system according to claim 6, wherein the vehicle control module is configured such that it: measures the point density of the point cloud array at a current index; and compares the point density with a defined point density threshold. [8] Lidar system according to claim 7, wherein the vehicle control module is configured to provide the multiplexed point cloud to the perception stack in response to the point density being greater than the specified point density threshold. [9] Method for operating a light-based detection and distance measurement (Lidar) system for a vehicle, the method comprising: Transmitting lidar signals at multiple frequencies via at least one lidar transmitter, wherein the at least one lidar transmitter is coupled to the vehicle and a parabolic reflector is positioned to reflect the lidar signals transmitted by the at least one lidar transmitter; Receiving, via multiple lidar receivers, lidar signals reflected from an environment around the vehicle, with each of the multiple lidar receivers receiving reflected lidar signals at a different frequency; Combining frequency data from reflected lidar signals received by multiple lidar receivers into a point cloud array; Generating a multiplexed point cloud according to the point cloud array; Providing the multiplexed point cloud to a perception stack configured to process three-dimensional images; and Automatic control of steering, acceleration and braking of the vehicle according to the multiplexed point cloud provided to the perception stack. [10] Light-based detection and distance measurement (Lidar) system for a vehicle, the Lidar system comprising: at least one transmitter configured to send lidar signals at multiple frequencies, wherein the at least one transmitter is coupled to the vehicle; multiple receivers configured to receive lidar signals reflected from an environment around the vehicle, each of the multiple receivers configured to receive reflected lidar signals at a different frequency; and a vehicle control module that is configured to: Frequency data from reflected lidar signals received at multiple receivers are combined into a point cloud array; a multiplexed point cloud is generated according to the point cloud array; the multiplexed point cloud is provided to a perception stack configured to process three-dimensional images; and automatically controls the steering, acceleration, and braking of the vehicle according to the multiplexed point cloud provided to the perception stack.

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