A pedal-enabled mechanical arm wide-range movement control method, system and medium

Abstract

A kind of mechanical arm wide-range movement control method, system and medium based on foot pedal enablement, a kind of method for decoupling management of hand control flow using foot enablement signal is proposed. The start-stop trigger signal is collected by foot switch, combined with state machine model and incremental mapping operator, the system can lock the pose of mechanical arm during the reset of hand controller, and realize the smooth incremental displacement superposition when re-engaging. The invention realizes the mechatronic decoupling of hand space input and foot logic control, effectively breaks through the space boundary of physical equipment, with the advantages of simple structure, smooth reposition, high control continuity.

Description

Technical Field

[0001] This invention relates to a method, system, and medium for controlling the large-range movement of a robotic arm based on foot-operated control, belonging to the field of teleoperation and multimodal human-machine interaction technology. Background Technology

[0002] With the rapid development of specialized robot technology, teleoperation has become an extension of human capabilities to perform operations in extreme or precise environments such as vacuum, high radiation, deep sea, and minimally invasive medical procedures. In modern master-slave bilateral teleoperation systems, the operator senses the physical characteristics of the slave environment through a master input device (such as a force feedback hand controller or a spatial position tracker) and issues posture control commands. To achieve high-precision operation, the master and slave ends typically employ position-to-position mapping or position-to-velocity mapping protocols.

[0003] However, in practical engineering applications, the asymmetry in the spatial dimensions of the master and slave ends constitutes a core technological bottleneck. The physical workspace of the master-end controller is limited by the length of its robotic arm and the physiological range of motion of the operator's arm, typically on the order of centimeters (such as the common 20cm×20cm×20cm space); while the task space of the slave-end robotic arm often covers several meters or even larger. This mismatch in workspace leads to the problem of limited motion boundaries in the master-slave control process.

[0004] To address the aforementioned spatial scale mismatch issue, existing technologies typically employ a pose relocation mechanism (Clutching Mechanism), which temporarily disengages the master-slave coupling via a logical clutch, allowing the operator to move the master device back to its physical center position before re-engaging it. Currently, the mainstream relocation triggering methods suffer from the following drawbacks: First, there's the manual triggering method based on the side buttons of the master handle. When performing highly sensitive tasks such as precision assembly or surgical suturing, the action of pressing buttons generates parasitic torque and physical vibration. This minute displacement is amplified synchronously to the slave end effector during master-slave mapping, causing unexpected pose deviations in the robotic arm and severely affecting the absolute accuracy of the operation. Furthermore, prolonged and frequent button pressing significantly increases operator finger muscle fatigue, reducing the system's continuous operating capability.

[0005] Second, there's the voice recognition-based control method. While voice control can free up your hands, it suffers from significant latency and low false recognition rates in noisy industrial environments or remote telemetry scenarios with limited communication bandwidth. For real-time motion control chains requiring millisecond-level response, delays in voice commands often lead to misalignment between master and slave mechanisms, and can even cause serious mechanical collisions.

[0006] Third, there is the simple start / stop based on traditional binary foot switches. Existing solutions of this kind are mostly coarse power or communication level disconnections, lacking deep coupling with high-level motion planning algorithms. When re-engaging control, due to the spatial pose deviation between the new initial position of the master device and the locked position of the slave robot, the system is prone to step displacement shocks, lacking smooth incremental transition logic and coordinate system realignment mechanisms.

[0007] In summary, existing technologies lack a continuous, large-scale control scheme that can achieve deep logical decoupling of the master-slave control chain, eliminate interference from hand-assisted operations, and possess smooth transition characteristics in motion trajectories. This limits the operational efficiency and safety of teleoperated robotic arms in complex, large-scale scenarios. Summary of the Invention

[0008] The technical problem solved by this invention is to address the various shortcomings of existing technologies by proposing a method, system, and medium for controlling the large-range movement of a robotic arm based on foot-operated enablement.

[0009] The present invention solves the above-mentioned technical problem through the following technical solution: A foot-enabled robotic arm large-range movement control method includes: Collect the mechanical pressing signal of the operator's foot switch, and obtain the start / stop enable command through signal preprocessing; Construct a finite state machine and execute transitions between different states within the finite state machine based on the edge-triggered signals of the start / stop enable instructions; Based on the real-time state of the finite state machine, determine the end-effector pose coordinates and corresponding spatial offset of the slave robot at the current moment, or update and superimpose the end-effector pose coordinates at the current moment. At the moment when the finite state machine is switching between two states, the hand control commands input by the operator's hand input device are interpolated and smoothed by a smoothing filtering algorithm. The processed incremental control commands are then used to drive the movement of the slave robotic arm.

[0010] The mechanical pressing signal of the foot switch is converted into a digital trigger signal, and the mechanical contact jitter is filtered out by a debouncing algorithm to generate a start / stop enable command. The debouncing algorithm uses a sliding time window debouncing algorithm: Set sampling frequency Build the time window width The system performs integration on the high-level and low-level states within the window, distinguishing when the continuous level state duration exceeds a preset trigger dead time threshold. The logic transition signal output at that time is used as the output signal.

[0011] The finite state machine includes two states for robotic arm control: control enable state and pose reset state. The real-time transition process based on the edge trigger signal is as follows: when the foot switch is pressed, if the rising edge of the current edge trigger signal is detected, the state machine transitions from the control enable state to the pose reset state. When the foot switch is released, if the falling edge of the edge trigger signal is detected, the state machine transitions from the pose reset state to the control enable state. In the pose reset state, the robotic arm calculates the spatial offset relative to the repositioning start point by locking the current end-effector pose coordinates; in the control enable state, the robotic arm maps and superimposes the end-effector pose coordinates through start / stop enable commands.

[0012] When the start / stop enable command instructs the robotic arm to enter the pose reset state, the current end effector pose coordinates of the slave robotic arm are locked. Simultaneously, it continuously acquires real-time pose data of the operator's hand input device within the physical workspace and calculates the spatial offset relative to the repositioning starting point. ; When the start / stop enable command instructs the robotic arm to enter the control enable state, the spatial offset calculated when the robotic arm last entered the pose reset state is extracted. As an incremental reference, the real-time motion data of the hand input device is superimposed onto the slave robot's pose coordinates locked when it last entered the pose reset state using an incremental mapping operator model. The robot arm pose is mapped and superimposed.

[0013] The incremental mapping operator model is as follows:

[0014] In the formula, for The target pose of the robotic arm is constantly controlled from the end effector. The absolute pose of the end-effector is determined at the instant it enters the pose reset state. Master-slave coordinate system transformation matrix; This is the motion scaling matrix; For the present The absolute coordinates of the hand input device at all times; To restore the repositioning start center coordinates of the hand input device at the control moment.

[0015] The operator's hand input device can be any one of a spatial hand controller, an inertial sensor data glove, or an optical tracking device; the smoothing filtering algorithm is a first-order hysteresis filtering algorithm.

[0016] In the formula, This is the smooth output instruction for the current cycle. This is the original calculation instruction for the current cycle. This is the output instruction for the previous cycle. These are the filter coefficients, and their values ​​range from [value range missing]. Dynamically adjust according to actual response needs To balance follow latency and smoothness.

[0017] A control system for implementing a motion control method includes a foot pedal enabling unit, a hand motion acquisition unit, a logic master control unit, and a slave robotic arm execution unit, wherein: The foot pedal enable unit has a built-in de-shake algorithm to collect foot pressing action data, and performs signal preprocessing according to the de-shake algorithm to generate start and stop trigger signals independent of hand operation, which are then transmitted to the logic main control unit. The hand motion acquisition unit acquires multi-degree-of-freedom position and posture data streams collected by the operator's hand input device in real time and transmits them to the logic main control unit; The logic master control unit, with a built-in finite state machine and smoothing filtering algorithm, receives start / stop trigger signals from the foot pedal enable unit and position data from the hand motion acquisition unit. It determines the real-time state of the finite state machine, determines the end-effector pose coordinates and corresponding spatial offset of the slave robotic arm at the current moment according to the current state, or updates and superimposes the end-effector pose coordinates at the current moment. At the moment of transition between the two states of the finite state machine, it performs interpolation and smoothing processing on the hand control commands input by the operator's hand input device through the smoothing filtering algorithm, and outputs the processed incremental control commands to the slave robotic arm execution unit. The slave robotic arm execution unit receives processed incremental control commands from the logic master control unit, and drives the robotic arm body to perform large-scale movement tasks through the incremental control commands.

[0018] The foot pedal enabling unit and the logic main control unit are connected via the USB HID protocol. The foot pedal enabling unit includes a foot switch and a communication conversion circuit, and as a standard human-machine interface device, it is mapped to logic key input through the communication conversion circuit.

[0019] The dual-state switching of the finite state machine is implemented through state machine switching logic, which is implemented through keyboard parsing node operation in the external robot operating system environment. The input state bit data of the foot switch is output after real-time synchronization through the standard topic communication mechanism of the communication conversion circuit.

[0020] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described control method.

[0021] The advantages of this invention compared to the prior art are: (1) The present invention provides a method, system and medium for controlling the large-range movement of a robotic arm based on foot-enabled operation, which can completely separate "state enable" and "pose input" at the physical operation level. The foot is responsible for the control of the logic gate, so that the hand can focus on the fine drawing of the spatial trajectory. This fundamentally eliminates the small displacement of the fingers and muscle tremors caused by traditional manual button triggering, realizes the decoupling of master and slave electromechanical logic, eliminates parasitic interference, and greatly improves the absolute positioning accuracy and continuous operation stability of the teleoperation system. (2) This invention uses mathematical coordinate locking and relative offset compensation calculation to seamlessly map the limited physical workspace of the master end (such as tens of cubic centimeters) into the infinite motion stroke of the slave end robotic arm through the cycle of "pose reset-reconnection". It constructs an incremental mapping mechanism, breaks through the physical space boundary, effectively overcomes the limitation of the asymmetry of the master and slave end spatial scale, and greatly expands the task adaptability range of the robotic arm. (3) This invention effectively prevents false triggering during operation by using hardware signal debouncing at the bottom layer and state machine management at the top layer. At the same time, the introduction of trajectory smoothing algorithms such as first-order hysteresis filtering overcomes the dynamic step impact caused by master-slave coordinate mismatch at the moment of clutch re-engagement, ensuring the equipment safety of the slave robotic arm in large-scale high-speed continuous operation, and realizing the software and hardware synergy to improve system safety and transition smoothness; (4) Based on the universal USB HID protocol and open-source robot operating system (ROS) topic communication architecture design, this invention can be quickly and seamlessly integrated into various multi-degree-of-freedom robotic arms and remote medical and aerospace remote operation platforms without any destructive hardware modification to the existing expensive high-precision hand controller (such as force feedback master hand). It has strong engineering application transformation value and can achieve high platform compatibility and extremely low deployment cost. Attached Figure Description

[0022] Figure 1 The finite state machine switching flowchart provided by this invention; Figure 2 This is a schematic diagram of the hardware system connection architecture provided by the present invention. Detailed Implementation

[0023] This invention discloses a method, system, and medium for controlling the large-range movement of a robotic arm based on foot-enabled operation. It proposes a method for decoupling and managing the hand control flow using foot-enabled signals. By acquiring start / stop trigger signals through a foot switch and combining a state machine model with an incremental mapping operator, the system can lock the robotic arm's pose during hand controller reset and achieve smooth incremental displacement superposition upon re-engagement. This invention achieves electromechanical decoupling between hand spatial input and foot logic control, effectively overcoming the spatial boundaries of physical devices, and possesses advantages such as simple structure, smooth repositioning, and high control continuity.

[0024] The execution flow of the foot-enabled robotic arm large-range movement control method is as follows: Collect the mechanical pressing signal of the operator's foot switch, and obtain the start / stop enable command through signal preprocessing; Construct a finite state machine and execute transitions between different states within the finite state machine based on the edge-triggered signals of the start / stop enable instructions; Based on the real-time state of the finite state machine, determine the end-effector pose coordinates and corresponding spatial offset of the slave robot at the current moment, or update and superimpose the end-effector pose coordinates at the current moment. At the moment when the finite state machine is switching between two states, the hand control commands input by the operator's hand input device are interpolated and smoothed by a smoothing filtering algorithm. The processed incremental control commands are then used to drive the movement of the slave robotic arm.

[0025] The mechanical pressing signal of the foot switch is converted into a digital trigger signal, and the mechanical contact jitter is filtered out by a debounce algorithm to generate a start / stop enable command. The debouncing algorithm uses a sliding time window debouncing algorithm: Set sampling frequency Build the time window width The system performs integration on the high-level and low-level states within the window, distinguishing when the continuous level state duration exceeds a preset trigger dead time threshold. The logic transition signal output at that time is used as the output signal.

[0026] The finite state machine includes two states for robotic arm control: control enable state and pose reset state. The real-time transition process based on edge-triggered signals is as follows: when the foot switch is pressed and the rising edge of the signal is detected, the state machine transitions from the control enable state to the pose reset state; when the foot switch is released and the falling edge of the signal is detected, the state machine transitions from the pose reset state to the control enable state. In the pose reset state, the robotic arm calculates the spatial offset relative to the repositioning start point by locking the current end-effector pose coordinates; in the control enable state, the robotic arm maps and superimposes the end-effector pose coordinates through start / stop enable commands.

[0027] When the start / stop enable command instructs the robotic arm to enter the pose reset state, the current end effector pose coordinates of the slave robotic arm are locked. Simultaneously, it continuously acquires real-time pose data of the operator's hand input device within the physical workspace and calculates the spatial offset relative to the repositioning starting point. ; When the start / stop enable command instructs the robotic arm to enter the control enable state, the spatial offset calculated when the robotic arm last entered the pose reset state is extracted. As an incremental reference, the real-time motion data of the hand input device is superimposed onto the slave robot's pose coordinates locked when it last entered the pose reset state using an incremental mapping operator model. The robot arm pose is mapped and superimposed.

[0028] The incremental mapping operator model is as follows:

[0029] In the formula, for The target pose of the robotic arm is constantly controlled from the end effector. The absolute pose of the end-effector is determined at the instant it enters the pose reset state. Master-slave coordinate system transformation matrix; This is the motion scaling matrix; For the present The absolute coordinates of the hand input device at all times; To restore the repositioning start center coordinates of the hand input device at the control moment.

[0030] The operator's hand input device can be any one of a spatial hand controller, an inertial sensor data glove, or an optical tracking device; the smoothing filtering algorithm is a first-order hysteresis filtering algorithm.

[0031] In the formula, This is the smooth output instruction for the current cycle. This is the original calculation instruction for the current cycle. This is the output instruction for the previous cycle. These are the filter coefficients, and their values ​​range from [value range missing]. Dynamically adjust according to actual response needs To balance follow latency and smoothness.

[0032] The control system that implements the motion control method comprises: The system comprises a foot pedal enabling unit, a hand motion acquisition unit, a logic master control unit, and a slave robotic arm execution unit, wherein: The foot pedal enable unit has a built-in de-shake algorithm to collect foot pressing action data, and performs signal preprocessing according to the de-shake algorithm to generate start and stop trigger signals independent of hand operation, which are then transmitted to the logic main control unit. The hand motion acquisition unit acquires multi-degree-of-freedom position and posture data streams collected by the operator's hand input device in real time and transmits them to the logic main control unit; The logic master control unit, with a built-in finite state machine and smoothing filtering algorithm, receives start / stop trigger signals from the foot pedal enable unit and position data from the hand motion acquisition unit. It determines the real-time state of the finite state machine, determines the end-effector pose coordinates and corresponding spatial offset of the slave robotic arm at the current moment according to the current state, or updates and superimposes the end-effector pose coordinates at the current moment. At the moment of transition between the two states of the finite state machine, it performs interpolation and smoothing processing on the hand control commands input by the operator's hand input device through the smoothing filtering algorithm, and outputs the processed incremental control commands to the slave robotic arm execution unit. The slave robotic arm execution unit receives processed incremental control commands from the logic master control unit, and drives the robotic arm body to perform large-scale movement tasks through the incremental control commands.

[0033] The foot pedal enable unit and the logic main control unit establish a connection via the USB HID protocol. The foot pedal enable unit includes a foot switch and a communication conversion circuit, and as a standard human-machine interface device, it is mapped to logic key input through the communication conversion circuit.

[0034] The finite state machine performs dual-state switching through state machine switching logic, which is implemented through keyboard parsing node operations in the external robot operating system environment. The input state bit data of the foot switch is output after real-time synchronization through the standard topic communication mechanism of the communication conversion circuit.

[0035] A computer-readable storage medium that stores a computer program that, when executed by a processor, implements a control method flow.

[0036] The following description, in conjunction with the accompanying drawings and preferred embodiments, provides further details: In the current embodiment, the execution flow of the foot-enabled robotic arm large-range movement control method is as follows: Figure 1 As shown: Step S1: Signal preprocessing. Collect the mechanical pressing signal of the operator's foot switch, convert it into a digital trigger signal, and use a debouncing algorithm to filter out mechanical contact jitter and generate a stable start / stop enable command. Step S2: State machine switching. Construct a finite state machine that includes a "control enable state" and a "pose reset state". Based on the edge trigger signal of the start / stop enable command, switch between the two states in real time. Step S3: Coordinate locking and offset calculation. When the system receives a start / stop enable command and enters the "pose reset state", it locks the current end effector pose coordinates of the slave robot arm. Simultaneously, it continuously acquires real-time pose data of the hand input device within its physical workspace and calculates its spatial offset relative to the repositioning start point. ; Step S4: Master-slave incremental mapping. When the system receives the start / stop enable command again and jumps back to the "control enable state", the spatial offset is extracted. As an incremental reference, the subsequent motion data of the hand input device is superimposed onto the locked slave robot pose coordinates using an incremental mapping operator. superior; Step S5: Smooth trajectory output. At the moment when the state machine jumps from "pose reset state" back to "control enable state", a smoothing filter algorithm is introduced to interpolate and smooth the hand control command, eliminating the step impact caused by the master-slave pose mismatch at the moment of repositioning, and outputting control commands to drive the slave robotic arm to move.

[0037] The signal preprocessing method is as follows: The hardware layer uses a mechanical contact foot switch to convert data into USB HID messages, while the software layer employs a sliding time window debouncing algorithm. The sampling frequency is set to... The time window width is The system integrates the high and low level states within the window and determines whether a continuous level is maintained for more than the dead time threshold (e.g., ...). Only when this condition is met can a valid logic transition be output, avoiding high-frequency erroneous switching of the state machine caused by mechanical contact vibration.

[0038] The calculation method for the incremental mapping operator is as follows: Establish the origin coordinate system of the Master Workspace. Base coordinate system with SlaveTask Space At the moment of control recovery, acquire the new starting center coordinates of the hand input device. In each subsequent control cycle In this process, the system calculates the target instruction using the following formula:

[0039] In the formula, for The target pose of the robotic arm is constantly controlled from the end effector. This is an absolute pose snapshot (i.e., anchor point coordinates) of the slave robot arm at the instant it enters the pose reset state. The master-slave coordinate system transformation rotation matrix is ​​used to align the three-dimensional orientation of the master and slave ends; This is the motion scaling matrix (usually a diagonal matrix); The current position of the hand input device in the coordinate system The absolute coordinates below.

[0040] The methods for trajectory smoothing and safe output are as follows: At the instant the state machine switches from the "pose reset state" to the "control enable state", due to the slight vibration of the main hand operation, the original command sequence is... Sudden changes may occur. A first-order lag filter operator is introduced for discretization and smoothing, where:

[0041] In the formula, This is the smooth output instruction for the current cycle. This is the original calculation instruction for the current cycle. This is the output instruction for the previous cycle. Filter coefficients (range of values) ), dynamically adjust according to actual response needs To balance follow latency and smoothness.

[0042] A control system for a foot-enabled robotic arm with a wide range of motion control includes: a foot-enabled unit, a hand motion acquisition unit, a logic master control unit, and a slave robotic arm execution unit, wherein: The foot pedal enable unit integrates a foot switch and a communication conversion circuit, and continuously sends non-interactive start / stop physical trigger signals to the main control unit. The hand motion acquisition unit uses a space hand controller or data glove with force feedback to read the operator's six-degree-of-freedom (6-DOF) position and attitude data stream in the workspace in real time; The logic control unit deploys control middleware based on the ROS architecture, internally running state machine management nodes, incremental mapping calculation nodes, and trajectory smoothing filtering nodes, receiving foot and hand data, and solving the above mathematical model in real time; The slave robotic arm execution unit receives a continuous and smooth sequence of instructions from the logic master control unit, drives the multi-degree-of-freedom joint servo motors, and performs large-range movement tasks.

[0043] Example 1: Foot-enabled robotic arm large-range movement control methods, such as Figure 1 , Figure 2 As shown, the specific steps include: (1) Building a hardware mapping environment: The master end uses a Geomagic Touch six-DOF force feedback master hand, and the slave end uses a seven-DOF collaborative robotic arm. The foot switch is connected to the logic master unit running Ubuntu and ROS Melodic via USB and is recognized as a standard button device.

[0044] (2) Establish master-slave heterogeneous mapping relationship: Based on the coordinate transformation relationship, calibrate the homogeneous transformation matrix from the master hand local coordinate system to the robot arm base coordinate system. And set the master-slave motion scaling ratio. .

[0045] (3) Execute state machine cycle scheduling: Based on the ROS node communication mechanism, listen to the / keyboard / keydown topic and maintain the global flag is_clutching.

[0046] (4) Achieve smooth transition and output: before re-enabling An internal first-order hysteresis filter is initiated to smooth the step command into an exponentially rising curve before sending it to the slave executor.

[0047] Among them, the system's underlying communication and timing control main loop (running frequency) The process is as follows: System Initialization: The control node is started in the ROS environment, issuing initial pose synchronization commands. The control state switching commands issued by the foot enable unit are encapsulated in the std_msgs / Bool standard message format containing timestamps. The master control node strictly ensures microsecond-level timing alignment between state switching and pose sampling by comparing timestamps. A "watchdog" mechanism is also introduced, with the master control unit using... The frequency sends heartbeat packets to the foot pedal enable unit. If the communication bus is physically disconnected at any time, the state machine will forcibly trigger a hardware interrupt, automatically switch to and lock in the "pose reset state" to prevent the risk of loss of control.

[0048] In the main control loop: Enable signal acquisition step: The level state of the foot switch is polled in real time, and after debounce within a time window, the finite state machine is updated. The pose stream published by the hand motion acquisition unit adopts the geometry_msgs / PoseStamped format, and the callback function queue length is set to 1 to ensure that the system always uses the latest frame data for calculation.

[0049] State determination and calculation step: If in "control enabled state", read the current coordinates of the hand controller. Substitute the values ​​into the incremental mapping operator formula to calculate the target coordinates after offset compensation. If in the "pose reset state", then It remains constant.

[0050] Smoothing Rendering and Velocity Clamping Step: The target pose is substituted into the first-order hysteresis filter equation to obtain the smoothed desired pose. Before deployment, the desired end-effector linear velocity is further calculated using differential methods. .like ,in To preset a safe speed threshold, a speed truncation algorithm is executed. The safe velocity is inversely integrated into the corrected target pose to ensure absolute safety within the kinematic envelope.

[0051] Command issuance step: Invoke the inverse kinematics solver to convert the target pose in Cartesian space into joint space commands, and issue them to the servo driver in real time via EtherCAT.

[0052] To address the problems in existing telecontrol systems, such as limited extreme positions, hand tremors caused by repeated zeroing, and the lack of smooth transition mechanisms and safety strategies, this invention and its embodiments can significantly break through the boundaries of the physical space of the master terminal, improve the overall control smoothness and absolute positioning accuracy of the system, and provide a solid technical foundation for large-scale aerospace teleoperation, remote force feedback precision operations, and medical robots.

[0053] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.

[0054] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for controlling the large-range movement of a robotic arm based on foot-operated enablement, characterized in that... include: Collect the mechanical pressing signal of the operator's foot switch, and obtain the start / stop enable command through signal preprocessing; Construct a finite state machine and execute transitions between different states within the finite state machine based on the edge-triggered signals of the start / stop enable instructions; Based on the real-time state of the finite state machine, determine the end-effector pose coordinates and corresponding spatial offset of the slave robot at the current moment, or update and superimpose the end-effector pose coordinates at the current moment. At the moment when the finite state machine is switching between two states, the hand control commands input by the operator's hand input device are interpolated and smoothed by a smoothing filtering algorithm. The processed incremental control commands are then used to drive the movement of the slave robotic arm.

2. The method for controlling the large-range movement of a robotic arm based on foot-enabled movement according to claim 1, characterized in that: The mechanical pressing signal of the foot switch is converted into a digital trigger signal, and the mechanical contact jitter is filtered out by a debouncing algorithm to generate a start / stop enable command. The debouncing algorithm uses a sliding time window debouncing algorithm: Set sampling frequency Build the time window width The system performs integration on the high-level and low-level states within the window, distinguishing when the continuous level state duration exceeds a preset trigger dead time threshold. The logic transition signal output at that time is used as the output signal.

3. The method for controlling the large-range movement of a robotic arm based on foot-enabled movement according to claim 2, characterized in that: The finite state machine includes two states for robotic arm control: control enable state and pose reset state. The real-time transition process based on the edge trigger signal is as follows: when the foot switch is pressed, if the rising edge of the current edge trigger signal is detected, the state machine transitions from the control enable state to the pose reset state. When the foot switch is released, if the falling edge of the edge trigger signal is detected, the state machine transitions from the pose reset state to the control enable state. In the pose reset state, the robotic arm calculates the spatial offset relative to the repositioning start point by locking the current end-effector pose coordinates; in the control enable state, the robotic arm maps and superimposes the end-effector pose coordinates through start / stop enable commands.

4. The method for controlling the large-range movement of a robotic arm based on foot-enabled movement according to claim 3, characterized in that: When the start / stop enable command instructs the robotic arm to enter the pose reset state, the current end effector pose coordinates of the slave robotic arm are locked. Simultaneously, it continuously acquires real-time pose data of the operator's hand input device within the physical workspace and calculates the spatial offset relative to the repositioning starting point. ; When the start / stop enable command instructs the robotic arm to enter the control enable state, the spatial offset calculated when the robotic arm last entered the pose reset state is extracted. As an incremental reference, the real-time motion data of the hand input device is superimposed onto the slave robot's pose coordinates locked when it last entered the pose reset state using an incremental mapping operator model. The robot arm pose is mapped and superimposed.

5. The method for controlling the large-range movement of a robotic arm based on foot-enabled movement according to claim 4, characterized in that: The incremental mapping operator model is as follows: In the formula, for The target pose of the robotic arm is constantly controlled from the end effector. The absolute pose of the end-effector is determined at the instant it enters the pose reset state. Master-slave coordinate system transformation matrix; This is the motion scaling matrix; For the present The absolute coordinates of the hand input device at all times; To restore the repositioning start center coordinates of the hand input device at the control moment.

6. The method for controlling the large-range movement of a robotic arm based on foot-enabled movement according to claim 4, characterized in that: The operator's hand input device can be any one of a spatial hand controller, an inertial sensor data glove, or an optical tracking device; the smoothing filtering algorithm is a first-order hysteresis filtering algorithm. In the formula, This is the smooth output instruction for the current cycle. This is the original calculation instruction for the current cycle. This is the output instruction for the previous cycle. These are the filter coefficients, and their values ​​range from [value range missing]. Dynamically adjust according to actual response needs To balance follow latency and smoothness.

7. A control system for implementing the motion control method of claim 4, characterized in that: It includes a foot pedal enabling unit, a hand motion acquisition unit, a logic master control unit, and a slave robotic arm execution unit, wherein: The foot pedal enable unit has a built-in de-shake algorithm to collect foot pressing action data, and performs signal preprocessing according to the de-shake algorithm to generate start and stop trigger signals independent of hand operation, which are then transmitted to the logic main control unit. The hand motion acquisition unit acquires multi-degree-of-freedom position and posture data streams collected by the operator's hand input device in real time and transmits them to the logic main control unit; The logic master control unit, with a built-in finite state machine and smoothing filtering algorithm, receives start / stop trigger signals from the foot pedal enable unit and position data from the hand motion acquisition unit, determines the real-time state of the finite state machine, determines the current end-effector pose coordinates and corresponding spatial offset of the slave robotic arm according to the current state, or updates and superimposes the current end-effector pose coordinates; and at the moment of transition between the two states of the finite state machine, it performs interpolation smoothing on the hand control commands input by the operator's hand input device through the smoothing filtering algorithm, and outputs the processed incremental control commands to the slave robotic arm execution unit; The slave robotic arm execution unit receives processed incremental control commands from the logic master control unit, and drives the robotic arm body to perform large-scale movement tasks through the incremental control commands.

8. The control system according to claim 7, characterized in that: The foot pedal enabling unit and the logic main control unit are connected via the USB HID protocol. The foot pedal enabling unit includes a foot switch and a communication conversion circuit, and as a standard human-machine interface device, it is mapped to logic key input through the communication conversion circuit.

9. The control system according to claim 8, characterized in that: The dual-state switching of the finite state machine is implemented through state machine switching logic, which is implemented through keyboard parsing node operation in the external robot operating system environment. The input state bit data of the foot switch is output after real-time synchronization through the standard topic communication mechanism of the communication conversion circuit.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When a computer program is executed by a processor, it implements the control method described in any one of claims 1 to 6.

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