41results about How to "Improve obstacle avoidance efficiency" patented technology

The invention provides a method and device for controlling multi-joint moving robot to avoid an obstacle. The method is characterized in that a vision guidance device and the infrared obstacle avoidance device are mutually coordinated to control the robot to move during the process that the robot moves from a starting point to a target point along a pre-planned global optimal route; when a vision system detects the obstacle in the preset distance, a robot base is stopped marching, the movement posture of each joint can be automatically adjusted by grade on the basis of a pre-constructed kinematic geometric model of each joint, and the joints can be swung, from a tail end performer to the base, within a feasible region of each joint, so as to avoid the obstacle by grade; a servo system can control the pose position of each joint and the chassis movement direction, so as to continuously control the robot to move toward the target point until the robot reaches the target point; the movement postures of each joint and the base can be synchronously adjusted during the infrared obstacle avoiding process, thereby avoiding subsequent repeated adjusting, and as a result, the obstacle avoiding efficiency of the multi-joint moving robot can be improved.

The invention belongs to the field of self-driving decision making technology, and provides a conic curve-based self-driving obstacle avoidance method, a conic curve-based self-driving obstacle avoidance device, an apparatus and a medium. According to the method, the obstacle information of an obstacle in front of a self-driving vehicle is obtained; a lateral relative distance between the self-driving vehicle and the obstacle is calculated according to the obstacle information, and a conic curve type adapted to the obstacle is determined; the safe area of the obstacle and the self-driving vehicle are delineated according to the determined conic curve type, so that a first short side radius and a second short side radius are obtained; when the lateral relative distance is smaller than the sum of the first short side radius and the second short side radius, the final desired attitude of the self-driving vehicle after obstacle avoidance is predicted; steering angular velocity required bythe obstacle avoidance of the self-driving vehicle is calculated according to the final desired attitude, so that the self-driving vehicle is controlled so as to complete obstacle avoidance; and therefore, the obstacle avoidance efficiency of conic curve-based self-driving obstacle avoidance can be improved, and the driving safety of self-driving can be improved.

The present invention discloses an obstacle avoiding method and device of a robot and the robot. The method comprises the following steps of obtaining an initial position and a target position on a map; determining a moving path with the initial position as a starting point and the target position as an end point and a plurality of track points arranged on the moving path in sequence; by using inertial navigation, tracking the multiple track points, so that the robot moves to the target position along the moving path; if the robot is detected to collide with an obstacle in a moving process, bypassing the obstacle; and determining position features in the process of bypassing the obstacle, comparing the position features with preset conditions corresponding to the position features to obtain a comparison result, and executing a bypassing strategy matched with the comparison result. In the way, the obstacle can be effectively avoided.

The invention discloses an unmanned vehicle emergency steering obstacle avoidance method based on obstacle motion prediction. A data acquisition module acquires road boundary information, real-time state information and obstacle information in the automobile driving process. Obstacle information is input into an obstacle motion prediction module; the obstacle motion prediction module predicts thelanding position and landing time of an obstacle to obtain corresponding data, the prediction data, the state information of the vehicle and the road boundary information are input into an unmanned vehicle obstacle avoidance track generation module to generate a corresponding steering obstacle avoidance trajectory, the generated obstacle avoidance trajectory data and the vehicle state informationare input into a neural network control module to solve a steering wheel angle required for the unmanned vehicle to track the steering obstacle avoidance trajectory, and the steering wheel of the unmanned vehicle is controlled to complete a corresponding obstacle avoidance task. According to the steering obstacle avoidance method, the unmanned vehicle can complete the emergency steering obstacle avoidance task when an obstacle suddenly falls down in front of the vehicle, and the driving safety of the unmanned vehicle and the rapidity of emergency steering obstacle avoidance are improved.

The invention relates to a sensor fusion and improved Q learning algorithm based dynamic barrier avoidance method. The method comprises the steps that S1) the safe distance to a barrier and target coordinate position information and scope during movement of a robot are set; S2) a present pose of the robot is determined, a navigation path is planned, and forwarding is started; S3) in the navigationprocess, environment data detected by a sonar sensor and environment data detected by a laser sensor are preprocessed and characterized and then fused to obtain environment data; S4) whether dynamicbarrier avoidance is needed for the present robot state is determined according to the fused environment data, if YES, a step S5) is carried out, and otherwise, a step S6) is carried out; S5) an improved Q learning dynamic barrier avoidance method is used to obtain the next motion state (a, theta); and S6) whether the robot reaches a target point is determined, if NO, the step S2) is returned to continue navigation, and otherwise, navigation is ended. The method can be used to overcome defects of the single sensor effectively, and improve the barrier avoidance efficiency in the dynamic environment.

The invention belongs to the technical field of automatic control, and discloses an obstacle avoidance trajectory planning method for a redundant mechanical arm based on an improved rapidly-exploring random tree. The method comprises the following steps of firstly, establishing a D-H model of the redundant mechanical arm and a simplified envelope model of an obstacle; secondly, according to the target pose of an end effector of the redundant mechanical arm, using an inverse kinematics analytical method of the redundant mechanical arm for solving a target joint angle meeting the requirement, and setting the target joint angle to be qgoal; thirdly, mapping the simplified envelope model of the obstacle to a joint space of the redundant mechanical arm, and further obtaining a collision-free free space of the redundant mechanical arm in the joint space; and fourthly, establishing a search tree in the collision-free free space by taking a node corresponding to the target joint angle qgoal as a target node, conditionally selecting a random sampling node according to a selection rule, introducing a search tree node screening mechanism, and finally planning a collision-free path in the collision-free free space.

The invention discloses a multi-agent cluster obstacle avoidance method based on reinforcement learning. The method comprises the following steps: S1, establishing a motion model of a cluster system; S2, defining an obstacle avoidance factor xi and an obstacle avoidance evaluation criterion; S3, designing a state space, a behavior space and a reward function trained by a cluster formation transformation obstacle avoidance model Q-learning when ximin is less than ximin; S4, enhancing a state space, a behavior space and a reward function of learning training by the cluster autonomous collaborative obstacle avoidance model during design; S5, designing an agent behavior selection method; and S6, obtaining a Q value table obtained by training, and carrying out cluster autonomous collaborative obstacle avoidance based on the motion model defined in the S1. According to the invention, parameters such as an obstacle avoidance factor and an obstacle avoidance evaluation criterion are used for selection and judgment of an intelligent agent cluster obstacle avoidance model, and a Q-learning algorithm is combined to train a cluster autonomous collaborative obstacle avoidance model, so that an optimal cluster individual obstacle avoidance strategy and high obstacle avoidance efficiency are obtained.

The invention relates to a dynamic obstacle avoiding method based on combination of a neural network and a Q-learning algorithm, and belongs to the technical field of robots. The dynamic obstacle avoiding method comprises the steps: initialization setting is conducted on relevant parameters, wherein initialization on parameters of the neural network and relevant parameters of Q learning are included; iterative training is conducted according to environment obstacle data and initialized parameters; according to current environment obstacle information, a current state of a moving robot is calculated and judged, a Q value is calculated and updated, and meanwhile parameters of the neural network are fed back and updated; according to the state after the parameters are updated, whether or notmovement of the moving robot is safe or not is judged; whether or not an iteration number reaches up is judged, and whether or not training continues is determined; and whether or not a target point is reached is judged, if not, Q table construction is conducted by using the neural network, a new round of iterative training is conducted, and if the target point is reached, navigation is ended. According to the method, the defects that the calculation time is long, and the convergence speed is low are overcome, and the obstacle avoiding efficiency in a dynamic environment is effectively improved.

The invention discloses a robot control method, which comprises the steps that a binocular camera collects image information and transmits the image information to a control unit; a TOF sensor detectsobstacle information and transmits the obstacle information to the control unit; an IMU sensor collects IMU data and transmits the IMU data to the control unit; and the control unit controls the robot to execute different actions in different working modes according to the image information, the obstacle information and the IMU data. According to the invention, the accuracy of acquiring obstacleinformation by the robot is improved, the visual blind area range of the robot is reduced, obstacle avoidance and obstacle bypassing of the robot are efficiently controlled, and working efficiency ofthe robot is greatly improved.

A local obstacle avoidance walking method of a self-moving robot, comprising: step 100: the self-moving robot walks in a first direction, and when an obstacle is detected, the self-moving robot translates for a displacement M1 in a second direction perpendicular to the first direction, and step 200: determining whether the self-moving robot is able to continue to walk in the first direction after the translation, if a result of the determination is positive, the self-moving robot continues to walk in the first direction, and if the result of the determination is negative, the self-moving robot acts according to a preset instruction. The method enables the robot to accurately avoid a local obstacle, provides a concise walking route, shortens the determination time, and improves the working efficiency of the self-moving robot.

The invention discloses an unmanned obstacle avoidance driving method and terminal based on a laser radar and a UWB array. According to the method, the laser radar is started, and real-time positioning information is acquired according to the regional positioning coordinate system established based on the preset UWB array, so that the vehicle is controlled to run along the pre-acquired path track; according to point cloud data of a laser radar, obstacle identification is carried out, three-dimensional data of an obstacle and coordinates of the laser radar of the obstacle are acquired, UWB coordinates of the obstacle are calculated, whether obstacle avoidance is needed or not is judged, and if yes, an obstacle avoidance route is generated according to a preset obstacle avoidance algorithm when a vehicle is away from the obstacle by a preset distance, and the vehicle runs along the obstacle avoidance route until bypassing the obstacle and returning to the pre-acquired path track; according to the invention, automatic obstacle avoidance of unmanned tracking driving of the vehicle can be realized, judgment is carried out according to the position and height of the obstacle, unnecessary avoidance can be reduced, the obstacle avoidance efficiency is improved, and the system can run without a GPS and is more stable.

The invention discloses a robot walking path planning method, and belongs to the technical field of robot control. The planning method for the walking path of the robot comprises the steps: acquiring the space information, and generating the walking path according to the space information, wherein the robot moves according to the walking path; when the robot encounters an obstacle in the moving process, enabling the robot to judge the state of the obstacle, wherein the state comprises a static state or a dynamic state; and enabling the robot adopts a corresponding obstacle avoidance strategy according to the state of the obstacle. The problem that in the prior art, the obstacle avoidance efficiency is low due to the fact that the robot obstacle avoidance processing mode is single is solved, the robot walking path planning method is provided, the obstacle avoidance efficiency of the robot can be greatly improved by judging the obstacles in different moving states and correspondingly adopting different obstacle avoidance strategies, and the obstacle avoidance efficiency of the robot is greatly improved; therefore, the patrol efficiency of the robot is improved, and the moving safety of the robot is further ensured.

The embodiment of the invention discloses a vehicle obstacle avoidance method, a vehicle obstacle avoidance device, a vehicle obstacle avoidance system and a vehicle. The vehicle obstacle avoidance method comprises the steps of determining a detour direction of the vehicle according to a preset travel route and obstacle position information of the vehicle; determining a detouring starting point, adetouring turning point and a detouring ending point of the vehicle according to the minimum turning radius of the vehicle, the extension width of the obstacle in the detouring direction, the vehiclebody width of the vehicle, the safety distance between the vehicle and the obstacle and a preset advancing route; and controlling the vehicle to detour between the detour starting point and the detour turning point at a maximum steering angle in the first hour hand direction and detour between the detour turning point and the detour ending point at a maximum steering angle in the second hour handdirection to avoid an obstacle. By the adoption of the vehicle obstacle avoidance method, a short vehicle detouring track can be obtained, the vehicle can detour the obstacle only by steering at themaximum steering angle, it is guaranteed that the vehicle obstacle avoidance method is simple, the steering angle does not need to be adjusted in the advancing process, and the vehicle obstacle avoidance efficiency is improved.

The invention relates to a probability density-based unmanned aerial vehicle three-dimensional path obstacle avoidance system. The system is characterized in that the unmanned aerial vehicle three-dimensional path obstacle avoidance system comprises an information processing module, an attitude recognition module, an attitude adjustment module, an information acquisition module and an obstacle avoidance execution module, wherein the attitude recognition module, the attitude adjustment module, the information acquisition module and the obstacle avoidance execution module are all connected withthe information processing module; and the three-dimensional path obstacle avoidance system further comprises a wind speed detection module. With the system adopted, surrounding environmental parameters can be monitored in real time during the obstacle avoidance process of an unmanned aerial vehicle, the influence of wind speed in the flight state of the unmanned aerial vehicle on obstacle avoidance is considered; a drift quantity caused by wind is corrected, and the obstacle avoidance efficiency of the unmanned aerial vehicle is improved. The system has the advantages of reliable function, good real-time performance, easiness in implementation, and capacity of coping with a plurality of types of dynamic unknown environments.

The embodiment of the invention provides an autonomous robot, an obstacle avoidance method and device thereof and a storage medium. The obstacle avoidance method of the autonomous robot comprises thesteps that obstacle position points are detected when an operation task is executed according to a set walking path; forming an obstacle position point marking area according to the detected obstacleposition point, and updating the obstacle position point marking area as a probability value of the obstacle; forming a newly added obstacle area according to the obstacle position point marking areareaching the preset probability threshold; and updating the walking path according to the newly added obstacle area so as to avoid the newly added obstacle area. According to the embodiment of the invention, the obstacle avoidance efficiency of the autonomous robot for newly added obstacles can be improved.

The embodiment of the invention discloses an obstacle data processing method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the steps of obtaining a point cloud data set obtained by scanning of a target vehicle-mounted laser radar; performing clustering processing on the point cloud data in the point cloud data set to generate a first obstacle information set; generating a second obstacle information set according to the target deep learning model and the point cloud data set; generating an obstacle feature distance matrix; obtaining a third obstacle information set; obtaining a fourth obstacle information set; obtaining a fifth obstacle information set; obtaining a combined obstacle information set; and sending the combined obstacle information set to the target terminal for display. According to the embodiment, the accuracy of obstacle detection is improved.

The autonomous navigation method of the intelligent walking robot in the complex environment is optimized, the proposed solution not only can realize stable and efficient robot autonomous navigation, but also is greatly helpful for accurate operation of a mobile platform in the complex environment, and meanwhile, the robot is helped to develop towards strong artificial intelligence, so that the intelligent walking robot is more intelligent. The method mainly comprises the steps of building an intelligent walking robot platform based on the ROS, improving a narrow space white main navigation method of the intelligent walking robot, and improving a navigation obstacle avoidance method of the intelligent walking robot in a high-dynamic obstacle environment. Advantage direction scheduling coordination is added, independent movement is carried out before the robot carries out local route planning, a wider operation space is searched for to optimize autonomous navigation of the robot, the autonomous movement ability and robustness of the robot are improved through optimization operation, efficient navigation and obstacle avoidance in a complex environment are achieved, and the robot navigation efficiency is improved. The robot has more efficient and stable autonomous navigation capability, and the motion intelligence of the robot is greatly improved.

The invention discloses an aircraft obstacle avoidance method. The method comprises the following steps: acquiring point cloud data in an advancing direction of an aircraft; performing gridding processing on the point cloud data to obtain gridding point cloud data; determining an aircraft obstacle avoidance mode according to the gridding point cloud data; and adjusting flight parameters of the aircraft according to the aircraft obstacle avoidance mode. In the obstacle avoidance process of the aircraft, an environment map does not need to be constructed, the obstacle avoidance mode of the aircraft can be determined only by obtaining the point cloud data in the advancing direction of the aircraft, and obstacle avoidance of the aircraft is achieved according to the obstacle avoidance mode of the aircraft, that is, compared with the prior art, the method provided by the invention does not need to consume a certain time to construct a local map, the obstacle avoidance time of the aircraft is shortened, the quick and real-time obstacle avoidance of the aircraft is realized, and the obstacle avoidance efficiency of the aircraft is improved.

The invention relates to the technical field of intelligent household appliances, and provides a cleaning and obstacle avoidance method and device, electronic equipment and a storage medium. The method comprises the steps of performing path planning based on a map and first obstacle mark information of the map, and determining a first cleaning path; advancing based on the first cleaning path, and determining real-time information of the first obstacle marking information; and determining a second cleaning path based on the real-time information of the first obstacle mark information, and continuing to advance based on the second cleaning path. According to the invention, when the first obstacle marking information is not updated, the obstacle guidance advancing route can be effectively avoided, the obstacle which is encountered in the last work and is not changed in position does not need to be repeatedly detected and avoided, and the obstacle avoidance efficiency is improved. And through the real-time information of the first obstacle mark information during the current work, the detection can be carried out again when the change of the position of the obstacle is identified, so that the obstacle information can be updated in time.

The invention provides a method and device for controlling a multi-joint mobile robot to avoid obstacles. The method includes: using visual navigation and infrared obstacle avoidance when the robot moves from a starting point to a target point according to a pre-planned global optimal path Coordinate with each other to control the movement of the robot. When the vision system detects an obstacle within the preset distance, it will suspend the advancement of the robot base, refer to the pre-established kinematic geometric model of each joint, and automatically adjust the motion posture of each joint step by step. Swing the joint within the feasible area of ​​the joint, from the end effector to the base, avoid obstacles step by step, control the pose of each joint and the movement direction of the chassis through the servo system, and continue to control the robot to move to the target point until the robot reaches the target point. During the infrared obstacle avoidance process, the motion postures of each joint and the base are simultaneously adjusted to avoid subsequent repeated adjustments and improve the obstacle avoidance efficiency of the multi-joint mobile robot.

The invention discloses an unmanned obstacle avoidance method and terminal based on a laser radar and a GPS. The method comprises the following steps: starting a laser radar, and controlling a vehicle to run along a pre-collected path track according to current GPS information; carrying out obstacle identification according to point cloud data of a laser radar, obtaining three-dimensional data of an obstacle and a laser radar coordinate of the obstacle, calculating a GPS coordinate of the obstacle, judging whether obstacle avoidance needs to be carried out according to the GPS coordinate of the obstacle and the three-dimensional data, and if the obstacle avoidance needs to be carried out, when a vehicle is away from the obstacle by a preset distance, generating an obstacle avoidance route according to a preset obstacle avoidance algorithm, and the robot travelling along the obstacle avoidance route until the robot bypasses an obstacle and returning to the pre-collected path track. According to the invention, automatic obstacle avoidance of unmanned tracking driving of the vehicle can be realized, judgment is carried out based on GPS coordinates and three-dimensional data, whether the vehicle will be damaged is judged according to the position and height of the obstacle, unnecessary avoidance can be reduced, and the obstacle avoidance efficiency is improved.

A local obstacle avoidance walking method of a self-moving robot, comprising: step 100: the self-moving robot walks in a first direction, and when an obstacle is detected, the self-moving robot translates for a displacement M1 in a second direction perpendicular to the first direction, and step 200: determining whether the self-moving robot is able to continue to walk in the first direction after the translation, if a result of the determination is positive, the self-moving robot continues to walk in the first direction, and if the result of the determination is negative, the self-moving robot acts according to a preset instruction. The method enables the robot to accurately avoid a local obstacle, provides a concise walking route, shortens the determination time, and improves the working efficiency of the self-moving robot.

The invention belongs to the technical field of robot navigation, and discloses a robot line patrol navigation system based on machine vision. The system comprises a predetermined patrol line, a navigation mark parallel to the predetermined patrol line and a visual robot. The visual robot comprises a visual robot body; a visual image acquisition module, mounted on one side, close to the navigationmark, of the visual robot body and used for acquiring image information around the visual robot in three directions, wherein navigation mark image information or obstacle image information is collected in a first direction, obstacle image information is collected in the second direction and the third direction, the second direction is perpendicular to the first direction, the first direction is located between the second direction and the third direction, and the included angle between the first direction and the third direction is any one of 30-90 degrees; an image processing module; a maincontrol module. In conclusion, the system has the advantages of being simple in construction cost and high in navigation and obstacle avoidance accuracy.

The invention discloses an unmanned aerial vehicle obstacle avoidance method based on double bispin Lyapunov Vector field. The method comprises the steps that the flight constraint condition of an unmanned aerial vehicle is determined, and an obstacle safety circle is constructed; obstacle avoidance decision is carried out through the obstacle safety circle; and the optimal obstacle avoidance direction and a vector field rotation direction are determined to carry out obstacle avoidance. In order to improve the obstacle avoidance efficiency and shorten an obstacle avoidance path, the criterionof successful obstacle avoidance is redefined. In order to simplify the complexity of obstacle avoidance, an obstacle merge reconfiguration rule for avoiding multiple tiny obstacles is provided. The method can meet the dynamic constraint of the unmanned aerial vehicle, realizes static and dynamic obstacle avoidance, and realizes autonomous obstacle avoidance of the unmanned aerial vehicle in a dynamic unknown environment.

The invention discloses a shared control method of an EEG mobile robot in an unknown environment. The shared control method: firstly collect the EEG signals of the user's motor imagination, perform preprocessing and feature extraction, and automatically carry out the EEG signals on the left and right sides. Adapt to the linear summation of the weights to obtain the EEG-speed control signal; the mobile robot obtains the autonomous obstacle avoidance-speed control signal according to the autonomous path planning; the mobile robot receives the EEG-speed control signal and the autonomous obstacle avoidance-speed control signal Share control and drive in unknown environments. Compared with the existing invention, the present invention can control the linear velocity of the mobile robot with the EEG-speed control signal, control the direction of the linear velocity of the mobile robot with the autonomous obstacle avoidance-speed control signal, and make the driving process more stable through continuous shared control .

The embodiment of the present invention discloses a vehicle obstacle avoidance method, a vehicle obstacle avoidance device, a vehicle obstacle avoidance system and a vehicle. The vehicle obstacle avoidance method includes determining the detour direction of the vehicle according to the vehicle's preset travel route and obstacle position information; The minimum turning radius of the vehicle, the extension width of the obstacle in the direction of detour, the body width of the vehicle, the safety distance between the vehicle and the obstacle, and the preset travel route determine the starting point, turning point and end point of the detour of the vehicle ;Control the vehicle to detour along the first clockwise direction with the maximum steering angle between the detour starting point and detour turning point, and detour along the second clockwise direction between the detour turning point and detour end point at the maximum steering angle to avoid obstacles things. Using the above vehicle obstacle avoidance method can obtain a shorter vehicle detour trajectory, and the vehicle can avoid obstacles only by turning at the maximum steering angle, ensuring that the vehicle obstacle avoidance method is simple, and there is no need to adjust the steering angle during travel, improving Vehicle obstacle avoidance efficiency.

The invention relates to the technical field of robot control, in particular to an obstacle avoidance control method and system for a six-axis mechanical arm and a computer readable storage medium. The method comprises the steps: determining a key point set on a mechanical arm; controlling the mechanical arm to operate towards a target, obtaining point cloud data of a working space where the mechanical arm is located in real time, and determining obstacle point cloud according to the point cloud data; determining the shortest distance between the mechanical arm and the obstacle in real time according to the key point set and the obstacle point cloud, wherein the shortest distance is the distance between the nearest key point and the nearest obstacle point; and when the shortest distance is smaller than the set safety distance, controlling the mechanical arm to avoid obstacles in real time in the process of moving towards the target. The obstacle avoidance efficiency of the mechanical arm is improved through accurate and autonomous distance calculation.

An unmanned aerial vehicle control method, apparatus and device, and a storage medium, when controlling an unmanned aerial vehicle to fly according to a preset route, if an obstacle and the unmanned aerial vehicle are located at the same route segment included in the preset route, controlling the unmanned aerial vehicle to avoid the obstacle along a first detour route, and if the obstacle and theunmanned aerial vehicle are located at different route segments, controlling the unmanned aerial vehicle to avoid the obstacle. If yes, the unmanned aerial vehicle is controlled to avoid the obstaclealong a second detour route different from the first detour route, that is, when the relative positions of the unmanned aerial vehicle and the obstacle are different, the unmanned aerial vehicle can select different detour routes to avoid the obstacle, so that the flexibility of the unmanned aerial vehicle detour strategy is improved; the unmanned aerial vehicle can flexibly and automatically bypass the obstacle without frequent braking, so that the obstacle avoidance efficiency and the operation efficiency of the unmanned aerial vehicle are improved, and the requirements of a user on automation and intelligence are met.

The invention discloses intelligent mowing equipment. The intelligent mowing equipment comprises a main body, a walking mechanism, a collision detection module, an information acquisition module and a control unit, wherein a mowing assembly is connected with the main body, the walking assembly is used for driving the main body to move, the collision detection module is arranged in the main body and is configured to be capable of detecting the motion state change of the intelligent mowing equipment and generating an acceleration signal, the information acquisition module is electrically connected with the collision detection module and is configured to be capable of acquiring the acceleration signal, judging the position where the intelligent mowing equipment collides with an obstacle and generating a collision signal; the control unit is electrically connected with the information acquisition module and can control the walking assembly to drive the main body to move according to the collision signal. The intelligent mowing equipment is higher in obstacle avoidance efficiency and safer in operation.

The invention provides a robot walking route automatic obstacle avoiding method and system and a robot, and relates to the technical field of robots. The method is applied to the robot automatic obstacle avoiding system. The robot automatic obstacle avoiding system comprises a collecting module, a control module, a driving module and a steering module. The method includes the steps that the collecting module obtains the pavement information corresponding to the current walking position of the robot on the preset walking route in real time and sends the pavement information to the control module. A normal route and an obstacle are arranged on the preset walking route. The control module controls the driving module or / and the steering module according to the pavement information so as to adjust the robot to walk on the normal route. The robot obstacle avoiding efficiency can be improved.