High-precision anchor hole control system and method for building punching robot

Abstract

The high-precision anchor hole control system comprises a mechanical arm, an impact electric hammer and a PID controller, the real-time speed v (t) and the real-time depth h (t) are collected, the PID controller calculates the optimal speed Vopt (h (t)) and the minimum depth hsafe (v (t)) according to the real-time speed v (t) and the real-time depth h (t) to obtain the speed deviation ev (t) and the depth deviation eh (t), the speed deviation ev (t) and the depth deviation eh (t) are fused into the comprehensive deviation e (t), and the comprehensive deviation e (t) is calculated according to the optimal speed Vopt (h (t)) and the minimum depth hsafe (v (t)). And the target acceleration acmd (t) is obtained, the mechanical arm outputs propulsive force according to the target acceleration acmd (t), the mechanical arm generates new actual acceleration aact (t), and the speed is updated to be v (t + Ts) = v (t) + aact (t) Ts. According to the method, accurate control over the anchor depth is achieved through the optimal propelling speed algorithm models in different stages of the mechanical arm.

Description

Technical Field

[0001] This invention relates to a building electromechanical drilling robot, which achieves high-precision anchor hole quality in concrete substrates. It is a high-precision anchor hole control system and method for building drilling robots. Background Technology

[0002] Building electromechanical installation requires drilling holes in concrete ceilings or the sides of concrete beams to facilitate subsequent anchor bolt installation. Substandard anchor bolt holes can cause serious safety accidents such as electromechanical pipelines falling.

[0003] In existing technology, the drilling angle is controlled by an inclination sensor, and the drilling depth is controlled by a distance sensor. The basic operating procedure is to set the drilling depth according to project requirements. When the drill bit advances to the set depth, the distance sensor sends a signal to the robotic arm, which then stops advancing and retracts the drill bit to complete the drilling. After repeated testing, the drilling angle deviation met the standard, but the actual depth deviation failed to meet the standard. Analysis revealed the following problems with the existing technology: the surface of the concrete working components (slabs and beams) is actually uneven, and the laser distance sensor hits the component surface at an angle. Furthermore, the actual drilling point where the drill bit at the end of the robotic arm contacts the concrete has a positional deviation from the sensor's distance measurement point, causing the actual anchor hole depth deviation to exceed the allowable anchor depth deviation specified in the national industry standard JGJ 145-2013. mm quality requirements. Excessive or insufficient robotic arm advance speed can cause anchor depth deviations to exceed standard deviation requirements, failing to guarantee drilling quality to meet anchor bolt installation needs and creating safety hazards. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a high-precision anchor hole control system and method for building drilling robots with high drilling accuracy and high robustness.

[0005] A high-precision anchor hole control system for a building drilling robot according to the present invention includes a robotic arm, an impact hammer mounted on the robotic arm, and a PID controller. The PID controller begins calculating the anchor depth when the impact hammer contacts the concrete surface and causes displacement. The robotic arm continuously advances and sends feedback signals to the PID controller. When the set anchor depth value is reached, the advancement of the robotic arm stops. Precise control of the anchor depth is achieved through an optimal advancement speed algorithm model at different stages of the robotic arm's movement. The robotic arm collects real-time speed data. v ( t ) and real-time depth h ( t The data is transmitted to the PID controller, which then uses the acquired real-time speed data... v ( t ) and real-time depthh ( t ), calculate the optimal speed V opt ( h ( t and minimum depth h safe ( v ( t This leads to the speed deviation. e v ( t ) and depth deviation e h ( t ), and merged into a comprehensive deviation. e ( t The PID controller is substituted with the comprehensive deviation. e ( t ), calculate the three components of the PID controller: the proportional term P, the integral term I, and the derivative term D, and sum them to obtain the target acceleration. a cmd ( t The robotic arm accelerates according to the target. a cmd ( t The output propulsion force causes the robotic arm to generate a new actual acceleration. a act ( t ), causing the speed of the robotic arm to be updated to v ( t + T s )= v ( t )+ a act ( t ) T s ,in T s The sampling period of the PID controller, the next sampling period t + T s The PID controller then collects the updated real-time speed again. v ( t + T s ) and real-time depth h ( t + T s Repeatedly calculate the optimal speed V opt ( h ( t and minimum depthh safe ( v ( t This leads to a new speed deviation. e v ( t ) and new depth deviation e h ( t ), and merged into a new comprehensive deviation. e ( t The new target acceleration is calculated. a cmd ( t This allows for real-time dynamic adjustment of speed.

[0006] The high-precision anchor hole control system for a building drilling robot provided by the present invention also has the following auxiliary technical features: Further including the optimal speed V opt ( h ( t The model is represented as

[0007] in, h safe The safety depth is the minimum depth of the robotic arm before deceleration, expressed by the formula: h safe ( v ( t ))= v ( t ) T, where T is the robotic arm response time; k h The velocity coefficient; v max The maximum speed at which the robotic arm advances to drill holes in the concrete is specified.

[0008] Further including the comprehensive deviation e ( t The model is represented as

[0009] in, α , β This is the deviation weighting coefficient. α + β =1, priority safety then β > α Prioritize efficiency α > β ; The speed deviation ev ( t ) represents

[0010] The depth deviation e h ( t ) represents

[0011] T step h is the time between the motor receiving the deceleration command and the start of reducing the pulse frequency. step h is the displacement of the motor between receiving a deceleration command and the start of reducing the pulse frequency. step = v(t)·T step s step For single-step distance, k h Here, f(t) is the velocity coefficient, and f(t) is the initial pulse frequency. This represents the rate of change of frequency.

[0012] Further including the target acceleration a cmd ( t The model is represented as

[0013] in, K p This is the proportionality coefficient; K i The integral coefficient; K d These are the differential coefficients; For integration time variable, This is the time derivative of the deviation.

[0014] This further includes the target acceleration output by the PID controller. a cmd ( t If constraints are imposed, then a min ≤ a cmd ( t )≤ a max ,in, a min This is the maximum deceleration; a max This is the maximum acceleration.

[0015] Further including the scaling factor K pThe integral coefficients are obtained using an empirical trial-and-error method, and the steps are as follows: First, the integral coefficients are... K i =0, the differential coefficient K d =0, only the proportional term is retained, P controls, from the smaller... K p Initially, observe the convergence of the velocity. If the velocity converges slowly, gradually increase the speed. K p If the speed frequently overshoots, reduce... K p Until the speed has no overshoot and converges relatively quickly, at this point K p This is a preliminary suitable value.

[0016] Further including the integral coefficient K i The proportionality coefficient is obtained through empirical trial and error, and the steps are as follows: K p On a suitable basis, gradually increase the integral coefficient. K i If static error exists, increase K i If integral saturation occurs, reduce... K i Alternatively, an integral separation strategy could be added. Further including the differential coefficients K d The proportionality coefficient is obtained through empirical trial and error, and the steps are as follows: K p and the integral coefficient K i On a suitable basis, gradually increase the differential coefficients. K d If the speed fluctuates frequently, increase K d To suppress fluctuations; if the response speed slows down, reduce K d . A high-precision anchor hole control method for a building drilling robot provided by the present invention includes the following steps: S1. Input the borehole design depth and drill bit diameter, compare with the drill bit database, and determine the available drill bit models; S2. Check the installed drill bits and available drill bit models; S3. Confirm that the installed drill bit and the optional drill bit model are consistent. If not, select and replace the drill bit from the optional drill bit models. If yes, proceed to the next step. S4. Start the robotic arm and electric hammer to perform the drilling operation; S5. Propulsion robot arm and end hammer, calculate the optimal propulsion speed of the current stage in real time in stages to avoid drilling too deep or too shallow. The optimal speed correction algorithm model of robot arm is calculated in real time. S6. Once displacement occurs on the concrete surface, start calculating the anchor depth and control the robotic arm to continue advancing. S7. When the displacement value reaches the designed drilling depth, the displacement sensor sends a feedback signal to the robotic arm to stop advancing. S8. Withdraw the drill bit to complete the high-precision drilling operation.

[0017] The high-precision anchor hole control method and system for a building drilling robot provided by this invention has the following advantages compared with existing technologies: This invention abandons the distance measuring sensor approach and instead uses a robust displacement sensor installed at the electric hammer at the end of the robotic arm. Anchor depth calculation begins when the sensor contacts the concrete surface and causes displacement. The robotic arm continues to advance, and the displacement sensor feeds back signals to the arm. When the set anchor depth value is reached, the arm stops advancing. Precise control of the anchor depth is achieved through an optimal speed algorithm model for the robotic arm's advance at different stages. For depth deviations caused by the high-frequency reciprocating impact of the electric hammer, a depth deviation correction algorithm is derived by monitoring the impact frequency and current variation characteristics of the electric hammer. This establishes a high-precision depth control device, method, and system, achieving high-precision control of the robot's anchor hole quality. Actual testing shows that this system can control the anchor hole depth deviation within 2mm, fully meeting the standard deviation requirements. Attached Figure Description

[0018] Figure 1 This is a flowchart of the present invention.

[0019] Figure 2 This is the front view of the present invention. Detailed Implementation

[0020] To clearly illustrate the solutions in this invention, preferred embodiments are given below in conjunction with the accompanying drawings. The following description is merely exemplary and not intended to limit the application or use of this disclosure. It should be understood that throughout the drawings, corresponding reference numerals denote the same or corresponding parts and features.

[0021] like Figure 1 and Figure 2As shown, this invention provides a high-precision anchor hole control system for a building drilling robot, including a robotic arm 1, an impact hammer 4 mounted on the robotic arm 1, and a PID controller. The PID controller starts calculating the anchor depth when the impact hammer contacts the concrete surface and causes displacement. The robotic arm continuously advances and sends feedback signals to the PID controller. When the set anchor depth value is reached, the advancement of the robotic arm stops. Precise control of the anchor depth is achieved through an optimal advancement speed algorithm model at different stages of the robotic arm's movement. The robotic arm also collects the real-time speed of the anchor hole. v ( t ) and real-time depth h ( t The data is transmitted to the PID controller, which then uses the acquired real-time speed data... v ( t ) and real-time depth h ( t ), calculate the optimal speed V opt ( h ( t and minimum depth h safe ( v ( t This leads to the speed deviation. e v ( t ) and depth deviation e h ( t ), and merged into a comprehensive deviation. e ( t The PID controller is substituted with the comprehensive deviation. e ( t ), calculate the three components of the PID controller: the proportional term P, the integral term I, and the derivative term D, and sum them to obtain the target acceleration. a cmd ( t The robotic arm adjusts according to the target acceleration. a cmd ( t The output propulsion force causes the robotic arm to generate a new actual acceleration. a act ( t ), causing the speed of the robotic arm to be updated to v ( t + T s )= v ( t )+ a act ( t ) Ts ,in Ts The sampling period of the PID controller, the next sampling period t + T s The PID controller then collects the updated real-time speed again. v ( t + T s ) and real-time depth h ( t + T s Repeatedly calculate the optimal speed V opt ( h ( t and minimum depth h safe ( v ( t This leads to a new speed deviation. e v ( t ) and new depth deviation e h ( t ), and merged into a new comprehensive deviation. e ( t The PID controller is substituted with the new comprehensive deviation. e ( t ), calculate the proportional term P, integral term I, and derivative term D of the PID, and sum them to obtain the new target acceleration. a cmd ( t The robotic arm adjusts according to the new target acceleration. a cmd ( t The output propulsion force causes the robotic arm to generate a new actual acceleration. a act ( t This allows for real-time dynamic adjustment of the speed. The sampling and calculation process described above is repeated continuously to achieve real-time dynamic adjustment. The PID controller calculates the control quantity based on the system error using proportional, integral, and derivative parameters. Here, P represents proportional control, I represents integral control, and D represents derivative control. The actual acceleration... a act ( t The velocity is directly obtained from sensors on the robotic arm. Through the aforementioned control system, the deviation between the target acceleration and the actual acceleration is reduced, thereby achieving precise control of the propulsion speed. Real-time velocity of the anchor hole is collected. v ( t ) and real-time depth h ( tThis is achieved by corresponding sensors. See also Figure 2 In the diagram, 1 represents the robotic arm; 2 is a built-in current and frequency sensor used to detect the current and operating frequency of the hammer drill motor; 3 is an accelerometer used to detect actual acceleration; 4 is the impact hammer used for drilling operations; 5 is a displacement sensor used to detect the real-time drilling depth; 6 is a dust cover used to catch dust falling during drilling; and 7 is the concrete working surface.

[0022] I. Construction of Mathematical Model for Correction of Optimal Speed ​​Algorithm for Robotic Arm Propulsion Since the control of the drilling speed of the robotic arm needs to consider both the "real-time drilling speed" and the "anchor hole design depth", two independent PID controllers need to be designed to control the speed and depth respectively, and then the output is fused by weighting.

[0023] 1. Correction Formula for Optimal Speed ​​Algorithm Before modeling, it is necessary to clarify the calculation methods for two core reference quantities (optimal speed and anchor hole design depth), which are the sources of PID input deviation: Optimal velocity function V opt ( h ( t )): Indicates the current depth h ( t The ideal propulsion speed corresponding to the depth (the greater the depth, the higher the optimal propulsion speed, and vice versa) is determined using a "nonlinear saturation model":

[0024] in: h safe The safe depth (the minimum depth before the robotic arm decelerates) is calculated using the following formula: h safe ( v ( t ))= v ( t ) T, T This refers to the robotic arm's response time. k h For speed coefficient, v max Maximum speed (limit) for the robotic arm to advance through concrete drilling.

[0025] 2. Weighted fusion bias design To balance speed and depth simultaneously, the two deviations are weighted by a coefficient. α , β Integrating into "Comprehensive Deviation" e ( t ) α + β=1, priority safety then β > α Prioritize efficiency α > β ): e ( t )= α e v ( t )+ β e h ( t ) For example, if α =0.4 (efficiency weight) β =0.6 (safety weight), when the depth is too small ( e h ( t When the overall deviation is greater than 0, the overall deviation leans more towards "needing to slow down," prioritizing safety; when the depth is sufficient ( e h ( t When )≈0), the overall deviation is dominated by the speed deviation, and efficiency is prioritized.

[0026] After receiving the deceleration command, the motor needs to go through T step The pulse frequency only begins to decrease during this period. During this phase, the vehicle travels at a constant speed v(t), with a displacement of h. step = v(t)·T step . s step The single-step distance is the linear displacement (mm / step) generated by the mechanical structure when one pulse is received.

[0027] During the deceleration phase, the velocity is reduced from v(t) to 0 by decreasing the pulse frequency. Let the initial pulse frequency be f(t), and the final velocity be reduced to 0. The rate of frequency change is... (Descending at a constant speed), then: The speed deviation e v ( t ) represents

[0028] The depth deviation e h ( t ) represents

[0029] 3. Mathematical Model of PID Control Algorithm The PID control algorithm outputs the target acceleration by using a proportional term (P) to eliminate the current deviation, an integral term (I) to eliminate the static error, and a derivative term (D) to suppress overshoot. a cmd ( t The formula for a PID controller in the continuous time domain is:

[0030] in, K p This is the proportionality coefficient; K i The integral coefficient; K d These are the differential coefficients; This is the time variable for integration (used only in integration operations). Let be the time derivative of the deviation. In continuous time, the differential term is... The rate of change of the deviation, in discrete time, is approximately: The sampling period.

[0031] Analysis of the function of each parameter: proportionality coefficient K p Amplifying the current deviation results in a fast response, but excessive amplification can easily lead to overshoot. Integral coefficient K i Accumulate historical deviations to eliminate static errors; Differential coefficients K d It reflects the rate of change of deviation and suppresses abrupt changes in deviation.

[0032] 4. Output constraints (physical limitations) Because there is a physical upper limit to the acceleration / deceleration of the robotic arm during concrete drilling and propulsion, the PID output needs to be adjusted. a cmd ( t Apply constraints to prevent the robotic arm from exceeding its performance limits: a min ≤ a cmd ( t )≤ a max .in, a min This is the maximum deceleration; a max This represents the maximum acceleration. The initial velocity is 0, and the final velocity is 0.

[0033] II. Real-time process adjustment (closed-loop control) The core of PID control is a real-time closed loop of "sensing-calculation-execution-feedback", the specific process of which is as follows: The data-sensing robotic arm collects "real-time speed" data in real time. v ( t ")" and "real-time depth" h ( t The data is transmitted to the PID controller. This is known as "real-time speed." v ( t ")" and "real-time depth" h ( t ")" refers to the advancing speed and advancing amount of the robotic arm during anchor hole operation.

[0034] Deviation calculation and fusion controller based on the collected data v ( t ), h ( t ), calculate the optimal speed V opt ( h ( t Minimum depth h safe ( v ( t This leads to the speed deviation. e v ( t ), depth deviation e h ( t ), and merged into a comprehensive deviation. e ( t ).

[0035] The PID controller calculates the target acceleration and substitutes it into the overall deviation. e ( t ), calculate the P, I, and D components of the PID, and sum them to obtain the target acceleration. a cmd ( t ), and adjust to [ ] through output constraints. a min , a max Within the range.

[0036] Execution and speed update of the robotic arm according to a cmd ( t The output propulsion force causes the robotic arm to generate a new actual acceleration. a act ( t ), to update the speed to v ( t +T s )= v ( t )+ a act ( t ) T s .

[0037] Feedback closed loop next sampling period ( t + T s The controller collects the updated data again. v ( t + T s )and h ( t + T s Repeat steps 2-4 to achieve real-time dynamic adjustment of speed.

[0038] III. PID Parameter Tuning The performance of a PID controller depends on K p , K i , K d Proper parameter selection is crucial; improper parameter tuning can lead to control failure (such as excessive overshoot or slow convergence). We employ an empirical trial-and-error method, with the following steps: Initial parameter settings first K i =0, K d =0, only the proportional term is retained (P controls), from the smaller... K p Begin (e.g.) K p =0.2), observe the velocity convergence: if the velocity convergence is slow (the deviation persists for a long time), gradually increase... K p If the speed frequently overshoots (e.g., exceeding the optimal speed and then rapidly decreasing), reduce... K p Until the speed has no overshoot and converges relatively quickly (at this point) K p (This is a preliminary suitable value).

[0039] Introducing an integral term (PI control) in K p On a suitable basis, gradually increase K i (Initial value) K i=0.04): If a static error exists (the speed is still lower than the optimal speed after stabilization), increase... K i If integral saturation occurs (due to continuous increase in acceleration leading to severe velocity overshoot), reduce... K i Alternatively, an "integral separation" strategy can be added (the integral term is only activated when the deviation is small).

[0040] Introducing the derivative term (PID control) and gradually increasing it. K d (Initial value) K d =0.12): If velocity fluctuations are frequent (e.g., small changes in depth cause frequent adjustments in acceleration), increase... K d To suppress fluctuations; if the response speed slows down (e.g., acceleration adjustment lags when deviation increases), reduce... K d .

[0041] IV. Stability and Robustness Analysis PID control needs to ensure "deviation convergence" (i.e., e ( t (As the speed eventually stabilizes at its optimal value, and the depth deviation is controlled optimally, the result is 0). This can be verified using the Lyapunov stability criterion. 1. Stability Verification Define Lyapunov functions ,like V ( e ( t If the derivative of the function is always negative, then the system is stable. Substituting this into the PID formula, it can be proven that when... K p> 0, K i >0, K d When the deviation is ≥0, the system satisfies the asymptotic stability condition (the deviation eventually converges to 0).

[0042] 2. Conclusion In the optimal speed control of robotic arm punching, the core advantages of PID control are its simple structure, strong real-time performance, and high robustness. It eliminates the need for complex optimization solutions (such as dynamic programming) and allows for real-time speed adjustment through millisecond-level sampling. The key lies in: a) rationally designing the "speed-depth" weighted fusion deviation to balance efficiency and safety; b) scientifically tuning the PID parameters to avoid overshoot and static errors.

[0043] V. Actual calculation example of the algorithm for correcting the deviation of the robotic arm's optimal propulsion speed is as follows: (I) Setting Basic Parameters for the Example 1. Robotic arm control parameters Table 1

[0044] 2. PID controller parameters (after empirical tuning) Table 2

[0045] (II) Calculation Formula 1. Optimal velocity function V opt ( h ( t ))

[0046] The greater the depth, the closer the optimal speed is to the physical limit speed; when the depth is too deep, the optimal speed tends to 0.

[0047] 2. Security Depth h safe ( v ( t )) h safe ( v ( t ))= 0.003 v ( t ) 3. Overall Deviation e ( t ) e ( t )=0.4 ( V opt ( h ( t )) v ( t ))+0.6 ( h safe ( v ( t )) h ( t )) Between fusion speed and depth deviations, safety should be prioritized.

[0048] 4. PID output (target acceleration) a cmd ( t )) Discrete time domain (sampling period) Ts=0.1 s The PID formula (numerical integral / derivative) is as follows: a cmd ( k )= K p e ( k )+ K i T s ∑ i =0 ke ( i )+ K d T s e ( k ) e ( k 1) in: k For time step ( k =0,1,2,..., corresponding to time t =0,0.1,0.2,... s ), ∑ i =0 ke ( i ) represents the cumulative sum of the integral terms. Tse ( k ) e ( k 1) is the differential term (rate of change of deviation).

[0049] 5. Actual speed update The actual speed of the robotic arm is determined by both the target acceleration and physical constraints: v ( k +1)= v ( k )+min(max( a cmd ( k ), a min ), a max ) T s (III) Results Analysis 1. Acceleration Phase ( t =0 1 s ): The speed reaches the physical limit, and the depth is far greater than the safe depth.

[0050] Speed ​​change: The robotic arm accelerates gradually from an initial speed of 0 m / s under PID control with a maximum acceleration of 0.05 m / s², and approaches the limit speed of 0.03 m / s at 0.6 s. The static error is less than 0.005 m / s (the integral term effectively eliminates the error).

[0051] Actual depth: Real-time drilling depth increased from 0m to 0.02m.

[0052] 2. Steady Phase (t=1) 2s): The speed converges to the optimal value, and the depth approaches the safe depth.

[0053] Speed ​​variation: The robotic arm operates smoothly from the maximum speed of 0.03 m / s, with a static error of less than 0.005 m / s (the integral term effectively eliminates the error).

[0054] Actual depth: Real-time drilling depth increased from 0.02m to 0.06m.

[0055] 3. Deceleration phase (t=2) 2.2s): The velocity approaches 0, and the depth approaches the designed depth. Speed ​​change: The controlled robotic arm gradually decelerates from an initial speed of 0.03 m / s under PID control at a maximum deceleration of -0.1 m / s², approaching 0 m / s at 0.2 s. The static error is less than 0.005 m / s (the integral term effectively eliminates the error).

[0056] Actual depth: The actual drilling depth increased from 0.06m to 0.08m, reaching the design depth of the anchor hole.

[0057] It is worth noting that the variables involved in the description of this invention are explained in detail in the following table.

[0058] Table 3

[0059] See Figure 1 and Figure 2 The high-precision anchor hole control method for a building drilling robot provided in this invention includes the following steps: S1. Input the borehole design depth and drill bit diameter, compare with the drill bit database, and determine the available drill bit models; S2. Check the installed drill bits and available drill bit models; S3. Confirm that the installed drill bit and the optional drill bit model are consistent. If not, select and replace the drill bit from the optional drill bit models. If yes, proceed to the next step. S4. Start the robotic arm and electric hammer to perform the drilling operation; S5. Propulsion robot arm and end hammer, calculate the optimal propulsion speed of the current stage in real time in stages to avoid drilling too deep or too shallow. The optimal speed correction algorithm model of robot arm is calculated in real time. S6. Once displacement occurs on the concrete surface, the anchor hole depth calculation begins, and the robotic arm is controlled to continue advancing. S7. When the displacement value reaches the designed drilling depth, the displacement sensor sends a feedback signal to the robotic arm to stop advancing. S8. Withdraw the drill bit to complete the high-precision drilling operation.

[0060] The real-time calculation of the optimal speed correction algorithm model for the robotic arm is completed by the system described in the above embodiment.

[0061] In summary, the above descriptions are merely embodiments of the present invention and are used only to illustrate the principles of the invention, not to limit the scope of protection of the invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A high-precision anchor hole control system for a building drilling robot, comprising a robotic arm, an impact hammer mounted on the robotic arm, and a PID controller, characterized in that: The PID controller begins calculating the anchor depth when the impact hammer displaces upon contact with the concrete surface. The robotic arm continues to advance and sends feedback signals to the PID controller. When the set anchor depth value is reached, the robotic arm stops advancing. Precise control of the anchor depth is achieved through an optimal speed algorithm model for the robotic arm at different stages of its advance. The robotic arm also collects real-time speed data. v ( t ) and real-time depth h ( t The data is transmitted to the PID controller, which then uses the acquired real-time speed data... v ( t ) and real-time depth h ( t ), calculate the optimal speed V opt ( h ( t and minimum depth h safe ( v ( t This leads to the speed deviation. e v ( t ) and depth deviation e h ( t ), and merged into a comprehensive deviation. e ( t The PID controller is substituted with the comprehensive deviation. e ( t ), calculate the three components of the PID controller: the proportional term P, the integral term I, and the derivative term D, and sum them to obtain the target acceleration. a cmd ( t The robotic arm accelerates according to the target. a cmd ( t The output propulsion force causes the robotic arm to generate a new actual acceleration. a act ( t ), causing the speed of the robotic arm to be updated to v ( t + T s )= v ( t )+ a act ( t ) T s ,in T s The sampling period of the PID controller, the next sampling period t + T s The PID controller then collects the updated real-time speed again. v ( t + T s ) and real-time depth h ( t + T s Repeatedly calculate the optimal speed V opt ( h ( t and minimum depth h safe ( v ( t This leads to a new speed deviation. e v ( t ) and new depth deviation e h ( t ), and merged into a new comprehensive deviation. e ( t The new target acceleration is calculated. a cmd ( t This allows for real-time dynamic adjustment of speed.

2. The high-precision anchor hole control system for a building drilling robot as described in claim 1, characterized in that: The optimal speed V opt ( h ( t The model is represented as in, h safe The safety depth is the minimum depth of the robotic arm before deceleration, expressed by the formula: h safe ( v ( t ))= v ( t ) T, where T is the robotic arm response time; k h The velocity coefficient; v max The maximum speed at which the robotic arm advances to drill holes in the concrete is specified.

3. The high-precision anchor hole control system for a building drilling robot as described in claim 1, characterized in that: The comprehensive deviation e ( t The model is represented as in, α , β This is the deviation weighting coefficient. α + β =1, priority safety then β > α Prioritize efficiency α > β ; The speed deviation e v ( t ) represents The depth deviation e h ( t ) represents T step h is the time between the motor receiving the deceleration command and the start of reducing the pulse frequency. step h is the displacement of the motor between receiving a deceleration command and the start of reducing the pulse frequency. step = v(t)·T step s step For single-step distance, k h Here, f(t) is the velocity coefficient, and f(t) is the initial pulse frequency. This represents the rate of change of frequency.

4. The high-precision anchor hole control system for a building drilling robot as described in claim 1, characterized in that: The target acceleration a cmd ( t The model is represented as in, K p This is the proportionality coefficient; K i The integral coefficient; K d These are the differential coefficients; For integration time variable, This is the time derivative of the deviation.

5. The high-precision anchor hole control system for a building drilling robot as described in claim 1, characterized in that: The target acceleration output by the PID controller a cmd ( t If constraints are imposed, then a min ≤ a cmd ( t )≤ a max ,in, a min This is the maximum deceleration; a max This is the maximum acceleration.

6. The high-precision anchor hole control system for a building drilling robot as described in claim 4, characterized in that: proportionality coefficient K p The integral coefficients are obtained using an empirical trial-and-error method, and the steps are as follows: First, the integral coefficients are... K i =0, differential coefficient K d =0, only the proportional term is retained, P controls, from the smaller... K p Initially, observe the convergence of the velocity. If the velocity converges slowly, gradually increase the speed. K p If the speed frequently overshoots, reduce... K p Until the speed has no overshoot and converges relatively quickly, at this point K p This is a preliminary suitable value.

7. The high-precision anchor hole control system for a building drilling robot as described in claim 6, characterized in that: The integral coefficient K i The proportionality coefficient is obtained through empirical trial and error, and the steps are as follows: K p On a suitable basis, gradually increase the integral coefficient. K i If static error exists, increase K i If integral saturation occurs, reduce... K i Alternatively, an integral separation strategy could be added.

8. The high-precision anchor hole control system for a building drilling robot as described in claim 7, characterized in that: The differential coefficient K d The proportionality coefficient is obtained through empirical trial and error, and the steps are as follows: K p and the integral coefficient K i On a suitable basis, gradually increase the differential coefficients. K d If the speed fluctuates frequently, increase K d To suppress fluctuations; if the response speed slows down, reduce K d .

9. A high-precision anchor hole control method for a building drilling robot, characterized in that: Includes the following steps: S1. Input the borehole design depth and drill bit diameter, compare with the drill bit database, and determine the available drill bit models; S2. Check the installed drill bits and available drill bit models; S3. Confirm that the installed drill bit and the optional drill bit model are consistent. If not, select and replace the drill bit from the optional drill bit models. If yes, proceed to the next step. S4. Start the robotic arm and electric hammer to perform the drilling operation; S5. Propulsion robot arm and end hammer, calculate the optimal propulsion speed of the current stage in real time in stages to avoid drilling too deep or too shallow. The optimal speed correction algorithm model of robot arm is calculated in real time. S6. Once displacement occurs on the concrete surface, start calculating the anchor depth and control the robotic arm to continue advancing. S7. When the displacement value reaches the designed drilling depth, the displacement sensor sends a feedback signal to the robotic arm to stop advancing. S8. Withdraw the drill bit to complete the high-precision drilling operation.

10. The high-precision anchor hole control method for a building drilling robot as described in claim 9, characterized in that: The real-time calculation of the optimal speed correction algorithm model for the robotic arm is performed by the system described in any one of claims 1 to 8.

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