Smart actuation system for wrist throttle and brake levers for speed and braking control in handlebar-steered vehicles

Abstract

The present invention relates to an assistive system for automating acceleration, deceleration, and braking in handlebar steered vehicles with wrist throttle and brake levers. The system integrates AI, ML, and computer vision to create an adaptive control mechanism that learns from rider behavior and environmental conditions. It operates in two modes: training mode to capture rider behavior and auto mode where AI predicts and controls actuators. Riders can override auto mode anytime without disrupting performance. The system includes cloud-based diagnostics, remote monitoring, and real-time optimization. Computer vision enhances environmental awareness by detecting obstacles, traffic, and road conditions. This invention offers improved adaptability, safety, and scalability, making it ideal for modern vehicle systems.

Description

SMART ACTUATION SYSTEM FOR WRIST THROTTLE AND BRAKE LEVERS FOR SPEED AND BRAKING CONTROL IN HANDLEBAR-STEERED VEHICLESRelated Application

[0001] The present application claims priority from Indian Patent Application No. 202441004222, filed on 22 / 01 / 2024, the entire contents of which are hereby incorporated by reference.Technical Field

[0002] The present invention relates to the field of vehicular control systems and riderassist technologies for handlebar steered vehicles like two wheeled vehicles. More particularly, it involves the use of artificial intelligence (Al) and machine learning (ML) to automate speed control, braking, and decision-making processes, enhancing commuter safety, comfort, and efficiency in urban traffic conditions. The invention would improve commuter’s riding experience by auto controlling speed and braking of the vehicle.Background of Invention

[0003] Population influx and growth of major cities has led to two wheeled vehicles becoming commonly used as mode of transportation for many commuters and various delivery businesses. In urban environments, two-wheeled vehicle riders often endure prolonged exposure to stop-and-go traffic, leading to rider fatigue and safety concerns. Existing technologies such as manual throttle and braking systems require constant user input, which increases strain during extended commutes.

[0004] Although some advancements, such as basic cruise control systems and anti-lock braking systems (ABS), are available, they lack adaptive automation tailored for two-wheeled or three-wheeled vehicles navigating congested roads. Furthermore, current solutions do not leverage modern technologies like artificial intelligence (Al) and machine learning (ML) to provide dynamic, real-time adjustments to speed and braking based on traffic conditions.

[0005] There remains a significant need for an intelligent system that can automate and optimize the operation of throttle and brake levers, reducing rider strain, enhancing safety, and providing a smoother riding experience in urban traffic.Summary of Invention

[0006] The present invention relates to an advanced assistive system for automating the control of acceleration, deceleration, and braking of vehicles steered with handlebar withwrist throttle and brake levers, particularly electric or auto-gear shift vehicles. This invention integrates cutting-edge technologies such as artificial intelligence (Al), machine learning (ML), and computer vision, powered by advanced hardware like central processing units (CPU), graphics processing units (GPU), and other high-performance computing devices, to provide a highly adaptive control system. The system learns from the rider’s behavior and environmental conditions, while improving control precision and safety.

[0007] The invention incorporates cloud-based remote diagnostics and operational features, allowing continuous monitoring, performance analysis, and system updates from any location. It enables remote troubleshooting and fine-tuning, ensuring the system performs optimally at all times.

[0008] The invention includes actuators using electromagnetic device like a motor for controlling the wrist throttle and brake levers, control mechanisms for dynamically adjusting control signals based on real-time sensor data, and feedback mechanisms comprising position sensors, load sensors, temperature sensors on the actuators.

[0009] The invention incorporates a ranging system which utilizes one or more range sensors, such as LiDAR, radar, ultrasonic, or infrared sensors, to measure the distance between the vehicle and objects in its proximity. Additionally, the system incorporates speedmeasuring devices, such as a Hall sensor module mounted on the wheel, or other similar speed sensors, to measure the vehicle's speed. The Hall sensor module detects the wheel’s rotational speed, providing real-time feedback on the vehicle’s velocity. Other similar speedmeasuring devices, such as tachometers or encoders, may also be used to track the rotational speed and calculate the vehicle's speed. The ranging system integrates these speed measurements with distance data from the other sensors, providing the adaptive learning system with real-time information about the vehicle's speed, the relative position of objects, other vehicles, and obstacles. This data is processed and used to optimize throttle and brake operation, enabling the apparatus to adjust control signals based on the detected range, proximity to objects, and the vehicle's speed. This integration improves reaction times, decision-making, and overall control in dynamic environments, enhancing safety and responsiveness.

[0010] The invention operates in two modes: training mode, where it learns the rider's behavior, and auto mode, where AI / ML algorithms predict and control throttle and brake actuators based on learned patterns.

[0011] The invention includes computer vision capabilities, which process images and video data from high-resolution cameras to enhance environmental awareness and improve decision-making by recognizing obstacles, traffic conditions, and road characteristics in real time.

[0012] The invention is powered by an electrical battery like Lithium ion, likewise other types of batteries, including solid-state batteries, nickel-metal hydride (NiMH) batteries, sodium-ion batteries, and lead-acid can also be utilized via a power and battery management system. Also it can be capable of integrating with solar power, hydrogen fuel cells, and nuclear energy, ensuring adaptability to emerging energy technologies. This feature offers scalability, longer operational ranges, and reduced environmental impact, making the system more sustainable and versatile in a rapidly evolving energy landscape.

[0013] The technical problem addressed by the present invention is the need for an intuitive, adaptive, and efficient control system for vehicles that automates acceleration and braking using wrist throttle and brake levers. Current systems often lack the ability to dynamically adjust to a rider’s behavior, adapt to changing environmental conditions, and provide a smooth transition between automated and manual control.

[0014] Additionally, many existing systems fail to integrate environmental awareness, such as detecting obstacles, road conditions, and traffic, which are crucial for ensuring rider safety and comfort. There is also a need for systems that can continuously learn and adapt to the rider's style over time, while providing real-time diagnostics and remote monitoring.

[0015] Lastly, the integration of computer vision for real-time visual recognition of surroundings, such as detecting obstacles and understanding traffic patterns, is not commonly utilized in current actuation systems for vehicles, limiting the system's responsiveness and safety features.

[0016] The invention provides a solution to the above-mentioned problems by incorporating Al, ML, and computer vision technologies into a system that adapts to both the rider’s behavior and the environment in real time.

[0017] Al and ML Algorithms are used to continuously learn from the rider’s throttle and braking patterns, refining control over time for smoother acceleration, deceleration, and braking. This results in a personalized, more comfortable ride.

[0018] Computer vision significantly enhances environmental awareness by processing visual data from cameras (such as stereo cameras for depth perception and high-resolutionlarge aperture cameras for low-light image capture), enabling the system to anticipate and react to dynamic conditions, like obstacles or changes in traffic, which improves rider safety and responsiveness.

[0019] The cloud-based remote diagnostic system further enhances the invention by allowing continuous monitoring of performance data, enabling troubleshooting, and providing real-time feedback for improvements. It supports remote performance analysis, diagnostics, and even system updates, ensuring optimal operation of the system over time.

[0020] The system operates in two modes: In training mode, the system captures data related to the rider’s behavior (e.g., throttle movement, braking force) and environmental inputs (e.g., traffic, road conditions) to optimize the AI / ML model. In auto mode, the system uses the trained algorithms to control the wrist throttle and brake actuators, making real-time predictions about the rider’s needs and environmental factors.

[0021] The system can be installed as part of the vehicle’s handlebar assembly or set up as a clip-on kit, providing flexibility as per the rider’s needs. Additionally, the invention features manual override, allowing the rider to take control at any time, with adaptive learning system learning from these manual interventions for future adjustments.

[0022] The Advantages of the invention are broadly classified below:

[0023] Enhanced Adaptability: The invention provides an adaptive system that learns from the rider's behavior over time, allowing the vehicle’s control system to optimize acceleration and braking based on individual preferences, improving the comfort and efficiency of the ride.

[0024] Seamless Mode Transition: The system facilitates a smooth transition between automatic control and manual override, offering flexibility for the rider while maintaining safety and ease of use. This allows the rider to assume control at any time without disrupting system performance.

[0025] Environmental Awareness: By incorporating computer vision, the system enhances its awareness of the surrounding environment. It processes data from cameras to detect obstacles, traffic patterns, and road conditions, significantly improving safety and providing better decision-making during dynamic riding scenarios.

[0026] Real-Time Learning and Optimization: The combination of Al and ML allows the system to continuously learn from the rider’s actions and environmental changes. This real-time learning and optimization result in smoother operation, more accurate control, and higher precision in throttle and braking adjustments.

[0027] Cloud-Based Diagnostics and Remote Monitoring: The cloud-based feature of the system provides the advantage of real-time performance monitoring, remote diagnostics, and software updates. This ensures the system can be continuously fine-tuned and optimized for long-term use, leading to improved reliability and performance over time.

[0028] Improved Safety and Comfort: The integration of adaptive control and real-time environmental awareness leads to enhanced safety features, including obstacle detection and traffic awareness, while also ensuring the ride remains smooth and comfortable for the rider.

[0029] Flexible Installation: The system is designed for easy installation, whether integrated directly into the vehicle’s handlebar assembly or as a modular, clip-on kit. This versatility ensures compatibility with a wide range of vehicle types and provides ease of use for riders.

[0030] User Feedback and Control: The inclusion of a user interface that provides feedback on system performance allows the rider to make informed adjustments. This feature ensures the system aligns with the rider’s preferences and needs, improving the overall user experience.

[0031] Scalability and Future-Proofing: With its cloud-based infrastructure, the system can scale and evolve over time. It can integrate new technologies, learn from new data sources, and adapt to various use cases and rider preferences, ensuring it remains effective as technology and user needs progress. The invention can also be integrated into futuristic vehicle designs, such as Star Wars-inspired speeder bikes, hover bikes, or similar advanced transportation systems, ensuring compatibility with next-generation mobility solutions and expanding its applicability across a wide range of vehicle platforms. Additionally, the system can integrate fleet control capabilities, enabling centralized management of multiple vehicles. This feature supports real-time monitoring, performance optimization, and coordinated operations for fleets, making it ideal for applications such as ride-sharing services, logistics, and autonomous vehicle networks.

[0032] Increased Responsiveness: The combination of Al, ML, and computer vision provides an exceptionally responsive system that adapts to both the rider’s behavior and environmental changes in real time. This ensures the vehicle’s controls react quickly and accurately, contributing to a safer and more enjoyable riding experience.

[0033] Renewable and Advanced Power Sources: The system is also capable of integrating with solar power, hydrogen fuel cells, and nuclear energy, ensuring adaptability to emerging energy technologies. This feature offers scalability, longer operational ranges, and reduced environmental impact, making the system more sustainable and versatile in a rapidly evolving energy landscape.Brief Description of Drawings

[0034] Some embodiments of the present invention are shown as examples and are not limited to the figures in the accompanying drawings. In the drawings, like references may indicate similar elements.

[0035] Fig.l illustrates an exploded perspective view of one example of a wrist throttle actuator, in accordance with various embodiments of the present invention.

[0036] Fig.2 illustrates an exploded perspective view of one example of a brake lever actuator, in accordance with various embodiments of the present invention.

[0037] Fig.3 illustrates a perspective view of one example of harness with buttons to operate the wrist throttle actuator and the brake lever actuator, in accordance with various embodiments of the present invention.

[0038] Fig.4 illustrates a perspective view of one example of the configuration of the harness with control console, the wrist throttle actuator, brake lever actuator and their respective buttons mounted on a vehicle, in accordance with various embodiments of the present invention.

[0039] Fig.5 illustrates the signal flow drawing for the train mode for the embodiment presented in Fig.4.

[0040] Fig.6 illustrates the signal flow drawing for the auto mode for the embodiment presented in Fig.4.

[0041] Fig.7 illustrates the signal flow drawing for the various components within the control console 31, as referenced in Fig.4, Fig. 10 and Fig. 11.

[0042] Fig.8 illustrates an exploded perspective view of the preferred embodiment of the wrist throttle actuator, in accordance with various embodiments of the present invention.

[0043] Fig.9 illustrates an exploded perspective view of the preferred embodiment of the brake lever actuator, in accordance with various embodiments of the present invention.

[0044] Fig.10 illustrates a perspective view of the preferred embodiment of the fully assembled invention, in accordance with various embodiments of the present invention.

[0045] Fig.11 illustrates another perspective view of the preferred embodiment of the fully assembled invention, in accordance with various embodiments of the present invention.

[0046] Fig.12 illustrates the signal flow drawing for the train mode for the preferred embodiment presented in Fig. 10 and Fig. 11.

[0047] Fig.13 illustrates the signal flow drawing for the auto mode for the preferred embodiment presented in Fig. 10 and Fig. 11.

[0048] Fig.14 illustrates the communication of the invention via the Control Console (31) with the cloud infrastructure over the internet.Description of Embodiments

[0049] At The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well as the singular forms, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof.

[0050] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one having ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0051] In describing the invention, it will be understood that a number of techniques and steps are disclosed. Each of these has individual benefit and each can also be used in conjunction with one or more, or in some cases all, of the other disclosed techniques. Accordingly, for the sake of clarity, this description will refrain from repeating every possible combination of the individual steps in an unnecessary fashion. Nevertheless, the specificationand claims should be read with the understanding that such combinations are entirely within the scope of the invention and the claims.

[0052] In the invention of the smart actuation system to auto control speed and braking of the vehicle via wrist throttle and brake levers while also providing seamless transition to manual control. The components and their positioning are discussed herein. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be evident, however, to one skilled in the art that the present invention may be practiced without these specific details.

[0053] The present disclosure is to be considered as an exemplification of the invention, and is not intended to limit the invention to the specific embodiments illustrated by the figures or description below.

[0054] The present invention will now be described by referencing the appended figures, which represent two embodiments of the invention. While the first embodiment illustrates one of the possible techniques, the second embodiment represents the preferred implementation of the invention.

[0055] Referring now to Fig. 1, which depicts an exploded perspective view of the wrist throttle actuator, illustrating components and features that may be included in various possible embodiments. In this embodiment, a steel cable (8) is clamped between the wrist throttle grip pulley (4) and wrist throttle grip pulley cover (5). The steel cable (8) is also clamped between motor pulley (6) and motor pulley cover (7). The steel cable (8) runs through the channels on the wrist throttle grip pulley (4), wrist throttle grip pulley cover (5), motor pulley (6), motor pulley cover (7) and is secured with cable nipples via holes provided on the wrist throttle grip pulley (4), wrist throttle grip pulley cover , motor pulley (6) and motor pulley cover (7).

[0056] The wrist throttle grip pulley (4), wrist throttle grip pulley cover (5), motor pulley (6) and motor pulley cover (7) are enclosed between the housing (9) and the housing cover plate (3). A high torque DC brushed geared motor (10) is mounted on housing (9). The shaft of the geared motor (10) passes through the housing into the motor pulley cover (7) and motor pulley (6) and secured with screws. The bracket (11) is screwed on the housing to mount the motor cover (12). The wrist throttle grip pulley (4) in the assembly slips over the vehicle wrist throttle (2). The assembled wrist throttle actuator (32) in mounted on the harness (34) via bracket (26) of the embodiment (Fig.4).

[0057] The steel cable (8), wrist throttle grip pulley (4), wrist throttle grip pulley cover(5), motor pulley (6), motor pulley cover (7) are all enclosed between housing (9) and the housing cover plate (3).

[0058] The vehicle’s wrist throttle (2) is mounted on the handle rod (1). The motor outer cover (12) attaches over the housing (9) via the bracket (11).

[0059] Referring now to Fig. 2, which depicts an exploded perspective view of the brake lever actuator, illustrating components and features that may be included in various possible embodiments. In the preferred embodiment the brake lever (13) is actuated via the steel cable (18). One end on the steel cable (18) is secured to the ball end of the lever via a clamp, wherein the clamp top (14) and clamp bottom (15) enclose the ball end along with the cable nipple. The other end of the steel cable (18) is also clamped between identical motor pulley(6) and motor pulley cover (7). The steel cable (18) similarly runs through the channels on the identical motor pulley (6), motor pulley cover (7) and over the bearing (17) with the other end also secured with cable nipples via holes provided on the identical motor pulley ( 6) and motor pulley cover (7).

[0060] The support bush (20) and sleeve (19) work collaboratively to securely mount the bearing (17) onto the handlebar grip (16), ensuring stability and proper alignment. The steel cable (18), support bush (20), sleeve (19), bearing (17), motor pulley (6), motor pulley cover(7) are all enclosed between similar housing (21) and the identical housing cover plate (3).

[0061] An identical high torque DC brushed geared motor (10) is mounted on housing (21). The shaft of the geared motor (10) passes through the housing into the identical motor pulley cover (7) and motor pulley (6) and secured with screws. The identical bracket (11) is screwed on the housing (21) to mount the identical motor cover (12). The assembled brake lever actuator (33) in the embodiment (Fig.4) is secured on the handlebar grip (16) and is also mounted on the harness (34) via bracket (27) in the embodiment (Fig.4).

[0062] Referring now to Fig.3, which illustrates a perspective view of the harness (34) in embodiment (Fig. 4), the components and features described herein, may be included in various embodiments. In the preferred embodiment, button (22), when pressed, energizes the wrist throttle actuator’s motor, initiating the rotation of the wrist throttle. Upon release of button (22), the motor is de-energized, allowing the wrist throttle to return to its default position. Additionally, button (23) is configured to log the duration for which the motor remains energized (ON) and de-energized (OFF) on the Control Console (31) in theembodiment (Fig. 4). In the training mode, simultaneous actuation of button (22) and button (23) enables the desired functionality of the wrist throttle actuator.

[0063] Similarly, button (25), when pressed, energizes the brake lever actuator’s motor, initiating the actuation of the brake lever. Upon release of button (25), the motor is deenergized, allowing the brake lever to return to its default position. Button (24) is configured to log the duration for which the motor remains energized (ON) and de-energized (OFF) on the Control Console (31) in the embodiment (Fig. 4). In the training mode, simultaneous actuation of button (24) and button (25) enables the desired functionality of the brake lever actuator.

[0064] The harness (34) of is also configured to serve as an auxiliary handlebar, providing an ergonomic grip point for the user, while simultaneously housing and supporting the components of the apparatus.

[0065] Referring now to Fig.4, which illustrates a perspective view of the fully assembled invention on the vehicle (35). The wrist throttle actuator (32), brake lever actuator (33), and their respective buttons are secured on the harness (34), which is bolted onto the vehicle at the rear-view mirror clamp point (30) using brackets (29) of the harness (Fig.3). The control console (31) is also affixed on the harness (34) via brackets (28) of the harness (Fig.3).

[0066] Referring now to Fig. 5, which illustrates the signal flow between the main components of the system in train mode, including a control console (31), a brake lever actuator (33), a wrist throttle actuator (32), DC brushed gear motors (10), and buttons (22), (23), (24), and (25). The control console (31) functions as the central processing unit, receiving input signals, managing operational logic, and transmitting output commands. These commands control the activation and deactivation of the DC brushed gear motors (10), thereby actuating the wrist throttle actuator (32) and the brake lever actuator (33) as required for operation.

[0067] Referring now to Fig. 6, which illustrates the signal flow between the main components of the system in auto mode, the control console (31) functions as the central processing unit, receiving input signals, managing operational logic, and transmitting output commands. These commands control the activation and deactivation of the DC brushed gear motors (10), thereby actuating the wrist throttle actuator (32) and the brake lever actuator (33) as required for operation.

[0068] Referring now to Fig. 7, which illustrates the signal flow within the control console (31) and its interaction with various system components. The control console (31) comprises a computer (36), a microcontroller module (38), and associated peripheral devices, integrated into a system capable of leveraging advanced technologies such as artificial intelligence (Al), machine learning (ML), and computer vision for enhanced performance and adaptability.

[0069] Input devices (43), such as a keyboard and mouse, allow the user to operate the console by sending commands to the computer (36). Additionally, the touch display (42) enables both system operation and real-time observation of ongoing processes. The computer (36) is further enhanced with Al-based user interfaces and multimodal interaction capabilities, allowing input through speech recognition, gesture control, and other intuitive methods. It also interfaces with cameras (37), which are equipped with computer vision algorithms for real-time image processing, object detection, and environmental analysis to improve decision-making .

[0070] The microcontroller module (38) collects data from speed sensors (39) and range sensors (40), which monitor the vehicle's behavior and surrounding environment. This data is further processed using ML algorithms on the computer (36) to analyze patterns, predict behaviors, and adapt system responses to specific conditions or user preferences. The processed information is utilized to train predictive models that improve system accuracy over time. The computer (36) subsequently communicates with and controls the motor control units (41) to execute the required mechanical functions with enhanced precision and adaptability.

[0071] The system incorporates real-time data logging capabilities, wherein operational data from sensors, cameras, and control units are continuously recorded. This data is transmitted to a cloud platform via a secure connection, enabling remote monitoring, advanced analytics, and integration with larger fleet management systems. The cloud platform also provides storage for historical data and allows periodic updates of Al and ML models based on aggregated data insights.

[0072] The bidirectional arrows in Fig. 7 represent communication pathways that ensure seamless coordination and synchronization among all components. This includes real-time feedback loops between the microcontroller module (38) and the computer (36) for adaptive control and between the cloud platform and the local system for periodic updates andadvanced diagnostics. This integration enables a highly efficient, intelligent, and adaptable system operation.

[0073] The system is further configured to operate as a multimodal platform, combining inputs from various sensors, user interfaces, and cameras into a unified decision-making framework. This multimodal integration ensures robust performance under diverse operating conditions and enhances the user experience through seamless human-machine collaboration.

[0074] The present invention will now be described with reference to the appended figures illustrating the second embodiment, which represents the preferred implementation of the invention. This embodiment exemplifies the use of Al, ML, computer vision, and cloud- enabled features for achieving an intelligent and adaptive vehicle control system.

[0075] Referring now to Fig. 8, it illustrates an exploded perspective view of the assembled wrist throttle actuator (67) in the preferred embodiment (Fig. 10). In this embodiment, an absolute magnetic encoder module (45) is mounted within the encoder housing (44) and enclosed by an encoder housing cover (46). The absolute magnetic encoder module (45) functions as a position sensor, precisely detecting the rotor position of the BLDC motor (49). The encoder housing cover (46) is attached to the motor bracket (47). The BLDC motor (49) features a hollow shaft, with its stator mounted onto the motor bracket (47). A torque transfer plate (51) is attached to the rotor and includes circumferential holes designed for calibration and configuration.

[0076] The torque generated by the rotor of the BLDC motor (49) is transferred to the wrist throttle grip (54) through the coupling bracket (50). The coupling bracket (50) includes projecting rods that pass through the holes on both the torque transfer plate (51) and the wrist throttle grip (54), securely coupling them together. This arrangement ensures the efficient transfer of torque to actuate the vehicle’s wrist throttle (2) of the embodiment (Fig. 1).

[0077] An encoder’s magnet (52) is mounted onto the magnet housing plug (53), which is inserted into one end of the wrist throttle grip (54). The opposite end of the wrist throttle grip (54) fits onto the vehicle’s wrist throttle (2) of the embodiment (Fig. 1).

[0078] A stack of three ferrite rings (48) is positioned between the absolute magnetic encoder module (45) and the hollow shaft of the BLDC motor (49). These ferrite rings effectively suppress noise caused by the electromagnetic interference generated by the BLDC motor (49).

[0079] The complete assembly of the wrist throttle actuator (67) in the preferred embodiment (Fig. 10) is mounted onto the vehicle via the motor bracket (47), which is secured to the bracket (26) of the harness (Fig. 3).

[0080] Referring now to Fig. 9, it illustrates an exploded perspective view of the assembled brake lever actuator (68) in the preferred embodiment (Fig. 10). Similarly, in this embodiment, an absolute magnetic encoder module (45) is mounted within the encoder housing (44) and enclosed by an encoder housing cover (46). Likewise, the absolute magnetic encoder module (45) functions as a position sensor, precisely detecting the rotor position of the BLDC motor (49). The encoder housing cover (46) is attached to the motor bracket (56). Likewise, the BLDC motor (49) also features a hollow shaft, with its stator mounted onto the motor bracket (56). A torque transfer plate (59) is attached to the rotor and includes circumferential holes designed for calibration and configuration.

[0081] The torque generated by the rotor of the BLDC motor (49) is transmitted to the brake lever through a series of interconnected components, including the torque transfer plate (59), brake lever torque plate (61), coupling bracket (57), triangular flange (62), linkage plate (63), ball-end adapter top (64), and ball-end adapter bottom (65). These components are secured and assembled using fasteners such as nuts, bolts, screws, bushes, and bearings, ensuring efficient torque transfer and structural stability.

[0082] Similarly, an encoder magnet (52) is mounted onto a magnet housing adapter (55), which is press-fitted through two stacked ferrite rings (48) and securely integrated into the rotor of the BLDC motor (45). As the rotor rotates, it drives the magnet housing adapter (55), causing the encoder magnet (52) to rotate. This rotational motion is captured by the absolute magnetic encoder, enabling precise position acquisition.

[0083] Within the rotor of the BLDC motor (49), one bearing (58) is press-fitted, while another bearing (58) is press-fitted into the torque transfer plate (59). When assembled, the two bearings are positioned in a stacked configuration, ensuring alignment and stability.

[0084] Additionally, another bearing (60) is press-fitted into the brake lever torque plate (61), which is mounted on the handlebar rod (66). The coupling bracket (57) is equipped with projecting rods that pass through the holes on both the torque transfer plate (59) and the brake lever torque plate (61), securely coupling them together. This arrangement ensures the efficient transfer of torque, enabling the actuation of the vehicle’s brake lever (13) through the interconnected components described above.

[0085] The complete assembly of the brake lever actuator (68) in preferred embodiment (Fig.10) is mounted onto the vehicle via the motor bracket (56), which is secured to the bracket (27) of the harness (Fig. 3).

[0086] Referring now to Fig. 10, it illustrates a perspective view of the preferred embodiment of the fully assembled invention mounted on the vehicle (35). The wrist throttle actuator (67), brake lever actuator (68) , are securely attached to the harness (34), which is bolted to the vehicle at the rear-view mirror clamp point (30) using brackets (29) on the harness (Fig. 3). The control console (31) is likewise mounted on the harness (34) using brackets (28) on the harness (Fig. 3). The battery (69) is provided to the power the invention.

[0087] Referring now to Fig. 11, it illustrates another perspective view of the preferred embodiment of the fully assembled invention mounted on the vehicle (35) along with the stereo camera (70) for depth perception.

[0088] Referring now to Fig. 12, which illustrates the signal flow between the main components of the system in train mode for the preferred embodiment, including a control console (31), a brake lever actuator (68), a wrist throttle actuator (67), BLDC motors (49), and position sensors (45). The control console (31) functions as the central processing unit, receiving input signals, managing operational logic, and transmitting output commands. These commands control the activation and deactivation of the BLDC motors (10), thereby actuating the wrist throttle actuator (67) and the brake lever actuator (68) as required for operation.

[0089] Referring now to Fig. 13, which illustrates the signal flow between the main components of the system in auto mode, the control console (31) functions as the central processing unit, receiving input signals, managing operational logic, and transmitting output commands. These commands control the activation and deactivation of the BLDC motors (10), thereby actuating the wrist throttle actuator (67) and the brake lever actuator (68) as required for operation.

[0090] Referring now to Fig. 14, which illustrates the communication between the Control Console (31) and the cloud infrastructure over the internet. The Control Console (31) acts as the local user interface, transmitting and receiving data to and from the cloud via a secure internet connection. The cloud infrastructure processes, stores, and manages the data, enabling remote monitoring and control of the system.Industrial Applicability

[0091] The present invention is applicable in a wide range of vehicles with a handlebar steering with wrist throttle and brake levers. It can also be used in assistive devices and mobility aids for riders with disabilities, offering a more adaptive, comfortable, and efficient riding experience.

Claims

AMENDED CLAIMS received by the International Bureau on 23 June 2025 (23.06.2025)1. An adaptive learning apparatus for automating the acceleration, deceleration and braking operation of a handlebar- steered vehicle with wrist throttle and brake levers, the apparatus comprising: a) one or more actuators configured for the automatic operation of the wrist throttle and brake levers; b) a computing system with memory; c) a multi-modal sensing system; d) a control system; e) a power system.

2. The apparatus of claim 1(a), wherein the actuators include electromagnetic motors capable of applying precise and incremental adjustments to the wrist throttle and brake levers, with integrated electromagnetic interference suppression devices to ensure stability of sensor outputs.

3. The apparatus of claim 1(a), wherein the actuators are operatively connected to a feedback mechanism allowing manual override, and are responsive to real-time control signals generated by the control system.

4. The apparatus of claim 1(b), wherein the computing system comprises one or more Neuromorphic Hardware, Quantum Computing Hardware, CPUs, GPUs, and memory modules, configured to execute control algorithms, store adaptive learning models, and process real-time sensor data.

5. The apparatus of claim 1(b), wherein the computing system includes a generative Al engine configured to synthesize and refine control strategies using feedback signals, behavioral inputs, and environmental data.

6. The apparatus of claim 1(c), wherein the multi-modal sensing system comprises one or more sensors selected from: optical sensors, range sensors, speed sensors, load sensors, and motion-related sensors configured to detect the state of motion.

7. The apparatus of claim 1(c), wherein the motion-related sensors are indirectly configured to measure rider behavior and vehicle state through changes in velocity, position, and directional forces.

8. The apparatus of claim 1(c), wherein the sensing system is configured to interpret environmental features, rider input behavior, and system feedback to inform adaptive control decisions.

9. The apparatus of claim 1(d), wherein the control system is configured to receive inputs from the sensing system and computing system, generate control commands for the actuators, and provide feedback signals to the rider.

10. The apparatus of claim 1(d), wherein the control system includes a closed-loop adaptive logic mechanism that uses rider responses to update the learning model stored in the computing system.

11. The apparatus of claim 1(d), wherein the control system delivers cues via one or more feedback mechanisms selected from: tactile vibrations, visual indicators, or audio alerts.

12. The apparatus of claim 1(e), wherein the power system includes one or more battery modules with a power management unit, optionally incorporating regenerative energy collection.

13. The apparatus of claim 1(e), wherein the power system is configured to provide consistent and isolated power to the actuators, computing system, sensing system, and control system to maintain real-time responsiveness.

14. The apparatus of claim 1, wherein the apparatus is cloud-connected to enable synchronization of learning models, diagnostics, and personalized rider feedback via mobile application.

15. The apparatus of claim 1, wherein the components are housed in a modular bolt-on unit for integration with the handlebar or chassis of the vehicle, optionally configured for concealed installation.

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