23716 results about "Rolling chassis" patented technology

To ensure the rigidity of a floor panel against a load in a vertical direction in an electric vehicle having a step in the floor panel.SOLUTION: A rear floor panel 10 of an electric vehicle has an inclined part 16 that extends while inclining upward as it heads for backward from a rear end of a plane part 12. A floor cross member 20 is disposed in a front part of the inclined part 16 on the side of an upper surface of the rear floor panel 10. An under-floor reinforcement 30 is disposed in the front part of the inclined part 16 on the side of a lower surface of the rear floor panel 10. A front end of the under-floor reinforcement 30 is disposed ahead of the front end of the inclined part 16, and a rear end of the under-floor reinforcement 30 is disposed on the inclined part 16. The under-floor reinforcement 30 and the floor cross member 20 are joined with the rear floor panel 10 therebetween.SELECTED DRAWING: Figure 6

A system to transport infant children is provided. The system includes a base configured to be secured to a portion of an automobile; a chassis independent from the base; a first release mechanism releasably coupling the chassis to the base; an infant car seat independent from the base and the chassis; a second release mechanism releasably coupling the infant car seat to the chassis; wherein the chassis and the infant car seat are releasable from the base as a combined unit upon operation of the first release mechanism; and wherein the infant car seat is releasable from the combined unit of the base and chassis upon operation of the second release mechanism.

An electrified fire fighting vehicle includes a chassis, a front axle coupled to the chassis, a rear axle coupled to the chassis, a water pump, an energy storage system, an engine, an electric motor coupled to the engine and the energy storage system, and a power divider positioned between the electric motor, the water pump, and the rear axle. The power divider facilitates selectively driving the water pump and the rear axle with the engine and the electric motor.

A vehicle includes a chassis including a frame rail extending longitudinally, a tractive element coupled to the chassis, a cab coupled to the chassis and configured to support an operator, an electric motor configured to drive the tractive element to propel the vehicle, a battery configured to supply electrical energy to the electric motor, a heat exchanger, a cable electrically coupling the electric motor and the battery, and a conduit fluidly coupling the battery and the heat exchanger. The cable and the conduit extend laterally from the battery to the frame rail, and the cable and the conduit extend longitudinally along the frame rail.

The invention provides a robot adaptive motion planning method and system based on compliance control, the method adopts admittance control as a compliance algorithm, the compliance is stronger compared with the traditional rigid control, and different compliance degrees can be selected according to the environment; combining inverse kinematics, trajectory interpolation and environmental parameters to construct an optimal reset trajectory under the constraint of a joint space safety region; by sensing external acting force and dynamically adjusting control parameters, the flexibility of the robot in a complex working environment is improved; a chassis-mechanical arm joint kinematics model is provided, and the problem that the working space of a traditional mechanical arm is limited is solved.

An auto-injector for administering a dose of a liquid medicament (M) is present having a tubular chassis telescopable in a tubular case, a carrier subassembly comprising a tubular carrier slidably arranged relative to the chassis inside the case, where the carrier is adapted to contain a syringe with a hollow injection needle. The injector also has a drive spring and a plunger for forwarding load of the drive spring to a stopper of the syringe, wherein the syringe is lockable for joint axial translation with the carrier. A control spring is arranged around the carrier for translating the carrier in a proximal direction (P) for insertion of the needle through the chassis into an injection site.

An auto-injector for administering a dose of a liquid medicament (M) is present having a tubular chassis telescopable in a tubular case, a carrier subassembly comprising a tubular carrier slidably arranged relative to the chassis inside the case, where the carrier is adapted to contain a syringe with a hollow injection needle. The injector also has a drive spring and a plunger for forwarding load of the drive spring to a stopper of the syringe, wherein the syringe is lockable for joint axial translation with the carrier. A control spring is arranged around the carrier for translating the carrier in a proximal direction (P) for insertion of the needle through the chassis into an injection site.

The invention relates to a dynamic load distribution method, device and equipment based on a vehicle body controller and a medium, and the method comprises the steps: collecting the mechanical load, electrical load and thermal load data of a vehicle body in real time through a distributed sensor network, and generating multi-source heterogeneous initial load data; performing standardization processing on the initial load data, and constructing a three-dimensional data cube type standard load data set; comprehensive characterization features are extracted through feature space mapping, and a fusion load feature set containing a threshold range is dynamically generated in combination with historical data; constructing a load correlation model based on the fusion features, and mapping to generate a steering and braking control parameter combination; and according to the real-time load threshold cross-border state, dynamically adjusting the task priority, allocating real-time calculation core resources to the chassis system, and generating an optimal allocation scheme. According to the method, the problems of multi-source load data fusion failure, resource allocation rigidity and safety task response delay in the prior art are solved, and dynamic load optimization of the vehicle body control system under complex working conditions is realized.

One variation of a system includes a modular kit. The modular kit includes: a driven axle configured to install on a bogie chassis supporting a trailer chassis of a trailer; a motor coupled to the driven axle; a battery assembly; a set of electrical cables; and a cable carrier. The battery assembly includes a set of retention features configured to transiently engage a set of engagement features on the trailer chassis to couple the battery assembly to the trailer chassis and is configured to: supply electrical energy to the motor to drive the driven axle; and receive electrical energy from the motor to regeneratively brake the driven axle. The set of electrical cables are configured to electrically couple the motor and the battery assembly. The cable carrier is configured to: locate between the bogie chassis and the battery assembly; and support the set of electrical cables over a range of longitudinal positions.

The invention relates to the technical field of robot intelligent control, in particular to a humanoid robot multi-modal environment sensing and self-adaptive chassis control method, which comprises the following steps: monitoring a contact force vector and a sliding trend in real time through a multi-dimensional touch sensor, mapping pose drift to a chassis coordinate system based on a Lie group constraint space-time synchronization layer, and performing multi-modal environment sensing and self-adaptive chassis control on the basis of a multi-dimensional touch sensor; a compensation vector is generated, a three-level tactile response layer dynamic switching force / bit mixed impedance mode is adopted, reverse translation of an omnidirectional chassis is combined to counteract drift, compensation parameters are optimized through a depth deterministic strategy gradient algorithm, and the system ensures control instruction time sequence alignment through a time-space stamp synchronization engine. The attitude oscillation in the compensation process is suppressed by using the inertial measurement unit, the obstacle avoidance interference domain is constructed based on the kinematics chain of the operation arm, and the compensation trajectory is smoothed by using the B-spline curve, so that the precision, stability and safety of the humanoid robot in the complex contact operation are improved, and an efficient and reliable solution is provided for a man-machine cooperation scene.

The invention relates to a wheel type double-arm humanoid robot motion track planning and obstacle avoidance method. The method comprises the steps that a robot system is started for self-inspection; the first sensor obtains environment information and constructs a real-time three-dimensional point cloud obstacle information graph; the second sensor obtains chassis state information and mechanical arm state information; a target task is set, and a moving path of a chassis and a moving path of a mechanical arm are planned based on the state information of the target task; and the system controls the chassis to move according to the planned moving path through the cooperative control model, and the mechanical arm moves according to the planned moving track. Through construction and real-time updating of the real-time three-dimensional point cloud obstacle information graph, the robot can effectively recognize and avoid obstacles, the risk of collision with the surrounding environment is reduced, meanwhile, the robot can adapt to the dynamically changing environment, path planning is rapidly updated through the D * Lite algorithm, and the path planning efficiency is improved. And the path can be adjusted in time when the obstacle moves or a new obstacle appears.

The invention relates to the technical field of automobile chassis simulation, and discloses an automobile chassis mechanism simulation optimization method based on digital twinning. The method comprises the following steps: firstly, acquiring a real-time operation data set of an automobile chassis mechanism, including multi-axis acceleration time sequence information, a suspension displacement monitoring sequence and the like, and synchronously transmitting the real-time operation data set to a cloud digital twin platform; constructing a hierarchical digital twin model comprising a suspension subsystem node, a steering mechanism node and a connecting component spatial constraint relation in the platform according to a chassis topological structure; performing multi-physics field feature extraction on the real-time operation data set to generate a chassis multi-physics field data set; executing multi-scale joint simulation calculation based on the model and the data set, and outputting a chassis dynamic response prediction result including fatigue damage distribution of the key connecting piece and the like; and finally, generating an optimization parameter adjustment instruction set according to the result, combining and feeding back to a physical chassis execution mechanism. According to the method, the real-time performance and precision of chassis simulation optimization are realized, and the chassis performance is improved.

The electronic apparatus includes a first chassis equipped with a first electronic component, a second chassis equipped with a second electronic component, a hinge device that relatively rotatably connects the first chassis and the second chassis, and a flexible board provided over the first chassis and the second chassis and connecting the first electronic component and the second electronic component. The flexible board has a first folded portion and a second folded portion that are disposed in order and curved in opposite directions to each other in the first chassis.

One example provides a chassis for an electric snowmobile including a battery pack. The battery pack includes a battery pack housing defining an enclosure for housing a number of battery modules for powering an electric motor of the electric snowmobile, the battery pack housing having a length extending in a longitudinal direction of the snowmobile, the battery pack housing including a bottom surface. A pair of opposing side panels extends downwardly from and along at least a portion of the length of the battery pack housing, the opposing panels and at least portions of the bottom surface of the battery pack housing together forming a rear structure extending in the longitudinal direction of the electric snowmobile.

The utility model provides a baby trailer with convenient storage, which comprises a trailer frame and a storage structure. The trailer frame comprises a front side frame, a rear side frame, a rear chassis frame. The front chassis frame is hinged with the front side frame. The rear chassis frame is hinged with the rear side frame. The storage structure is hinged with the front side frame and the rear side frame, so that the front frame and the rear side frame are capable of folded. The storage structure comprises two storage frames, a connecting rod. The connecting rod is connected with the left storage frame, the connecting rod is connected with the right storage frame. The ends of the front chassis frame and the rear chassis frame are movably placed on the connecting rod. The baby trailer has the advantages of convenient storage and small occupied space after storage.

A dynamic traffic environment-oriented multi-lane driving decision-making method based on reinforcement learning, comprising: using state space, action space, and trajectory sampling information in a multi-lane driving decision-making scenario to establish a decision-making neural network model; using a comprehensive reward function to perform reinforcement learning training on the decision-making neural network model; continuously and deeply sensing the surrounding environment by means of a sensor array with which a vehicle is equipped, and capturing sensed environment information; inputting the sensed environment information into the decision-making neural network model, and, on the basis of current environment information, the decision-making neural network model predicting a vehicle trajectory and a recommended driving operation within a period of time; and converting the recommended driving operation outputted by the decision-making neural network model into a specific control instruction, and sending the instruction to a drive-by-wire chassis and an actuator of the vehicle.

The invention discloses a welding positioning device for impeller machining and a positioning method thereof, and relates to the technical field of impeller machining, the welding positioning device comprises a workbench and a positioning assembly, the center of the top of the workbench is rotationally connected with a storage table, a rack is arranged at the outer end of the top of the workbench, and a lifting assembly is arranged in the middle of the rack; the positioning assembly is arranged at the outer end of the lower portion of the lifting assembly and comprises a polished rod, a limiting sleeve, a guide part, a rubber mat, a positioning spring, a baffle, a positioning rod and a tooth groove. After the impeller base plate is placed on the upper portion of the storage table, the limiting sleeve can be lifted, the blades are inserted into the bottom of the limiting sleeve, at the moment, the upper ends of the blades can be guided through the guiding part, the convenience of inserting the blades is improved, the shape of an inner groove of the limiting sleeve is matched with the shape of the blades, and therefore the blades can be conveniently inserted. And after the blade is placed, the positioning spring can push the baffle, so that the limiting sleeve tightly presses the blade on the impeller chassis.

The invention relates to a multi-sensor fusion positioning method suitable for a multi-axle steering vehicle, and the method comprises the following steps: S1, installing a plurality of sensors on a multi-axle all-wheel steering vehicle platform, collecting IMU data, a laser radar real-time scanning point cloud, a GNSS signal, the reading of each wheel angle sensor, and the reading of each wheel speed meter, and carrying out the real-time scanning of the IMU data, the laser radar real-time scanning point cloud, the GNSS signal, the reading of each wheel angle sensor, and the reading of each wheel speed meter; and the timestamps of all the collected signals are aligned. And S2, establishing a kinematic model of a to-be-estimated state, and performing distortion removal on the laser radar point cloud data according to the IMU data to realize motion compensation of the point cloud. And S3, establishing an error state discrete model, a laser radar observation model, a multi-axis steering vehicle kinematics observation model and a GNSS observation model. And S4, considering the influence caused by multi-wheel non-Ackerman steering, and providing a method for adaptively adjusting the observation noise covariance of the multi-axle steering vehicle so as to ensure the correct weighting of chassis observation data. And S5, fusing IMU, GNSS, laser radar, and rotation angle and rotation speed observation information of each wheel of the multi-axis steering vehicle, constructing a sequential iterative error state Kalman filter, and obtaining an optimal positioning estimation result through iterative calculation.

A vehicle includes a chassis including a first frame rail and a second frame rail, a tractive element coupled to the chassis, a drive motor configured to drive the tractive element to propel the vehicle, and an energy storage system. The energy storage system includes a first battery module and a second battery module. The energy storage system is selectively reconfigurable between (a) a first configuration in which the first battery module and the second battery module each provide electrical energy to the drive motor and (b) a second configuration in which the first battery module is removed from the vehicle and the second battery module provides electrical energy to the drive motor.

A modular system for drones is provided. A chassis can include a coupling mechanism operable to removably couple the chassis with a drone. A plurality of modular components can be operable to be interchangeably coupled with a control component. The modular components can be operable to be detachably coupled with a payload.

The invention belongs to the technical field of humanoid robots, and particularly relates to a heavy-load anti-explosion humanoid robot which comprises modular components and a multi-mode sensing network. The modular component comprises a movable chassis assembly used for providing omni-directional movement for the robot; the lifting assembly is fixed to the upper portion of the movable chassis assembly and used for providing lifting driving force; the body assembly is connected with the lifting assembly through the waist synchronous joint module and can be driven by the lifting assembly to ascend and descend; the head assembly is connected with the body assembly and cooperates with the lifting assembly to achieve visual field adjustment by configuring rotating modules in three directions; the multi-mode sensing network is distributed on the head assembly, the body assembly and the mobile chassis assembly through combination of a plurality of sensors in a space full-coverage strategy, and real-time obstacle cross validation, target positioning and obstacle and narrow channel detection in the space can be achieved. The problems that the target detection and obstacle avoidance effects of the robot are poor, the operation load is insufficient, and the operation range is small are solved.

A structural element for a motor vehicle chassis, particularly a chassis of an electrically powered motor vehicle, includes at least two securing sections and a central section which connects the two securing sections. Each securing section can be secured to an outer surface of a motor mounting element of the chassis and / or to an outer surface of a longitudinal member of the chassis.