基于大疆MSDK实现的无人机视觉引导自适应降落功能

基于大疆MSDK实现的无人机视觉引导自适应降落功能

概述

最初需求:想要无人机在执行完航线任务后,一键落到一个指定的位置,简化人工控制。

实现一套完整的无人机自主降落功能,通过虚拟摇杆控制使无人机飞向指定位置,再利用视觉识别引导无人机精确降落到具体位置。本文中采用自适应降落策略,根据高度动态调整精度要求和下降速度,以实现安全、精确的降落。

核心点:

  • 虚拟摇杆导航替代FlyTo功能
  • 双轴(X/Y)位置偏移实时调整
  • 高度自适应降落策略
  • 视觉识别引导定位
  • 智能避障管理

系统架构

整体流程

高于50m

20-50m

5-20m

低于5m

用户触发Return to Vehicle

获取无人机GPS位置

计算与目标点距离

启动虚拟摇杆导航

飞向目标位置 5m/s

距离小于10m?

开始自适应降落

视觉识别系统

计算X/Y偏移量

更新偏移量到ViewModel

自适应降落循环

高度分段判断

高空模式

中空模式

低空模式

极低空模式

计算调整速度和下降速度

偏移大于阈值2倍?

停止下降只调整

边调整边下降

高度小于5m?

关闭下视避障

高度小于等于0.1m?

着陆完成清理资源

技术实现思路

第一步:让无人机飞到目标位置?

问题分析

遥控器控制的无人机在执行完航线任务之后,飞到给定降落点(汽车或其他载具上)。最初的想法是使用DJI SDK提供的FlyTo功能,直接指定目标GPS坐标让无人机飞过去。但在实际测试中,发现部分机型(如M3E)并不支持FlyTo功能。

机型是否支持FlyTo功能参考文档https://developer.dji.com/doc/mobile-sdk-tutorial/cn/tutorials/intelligent-flight.html

解决方案:虚拟摇杆导航

既然FlyTo功能不可用,那就用虚拟摇杆功能进行模拟。

思路:

  1. 计算当前位置到目标位置的方位角(bearing)
  2. 将方位角转换为速度分量(南北/东西)
  3. 持续发送虚拟摇杆指令,让无人机朝目标飞行
  4. 实时监测距离,接近目标时停止

方位角计算:

privatefuncalculateBearing(latA: Double, lonA: Double, latB: Double, lonB: Double): Double {val lat1 = Math.toRadians(latA)val lat2 = Math.toRadians(latB)val dLon = Math.toRadians(lonB - lonA)val y = Math.sin(dLon)* Math.cos(lat2)val x = Math.cos(lat1)* Math.sin(lat2)- Math.sin(lat1)* Math.cos(lat2)* Math.cos(dLon)var bearing = Math.toDegrees(Math.atan2(y, x)) bearing =(bearing +360)%360// 归一化到0-360度return bearing // 0°=正北, 90°=正东, 180°=正南, 270°=正西}

速度分量计算:

val bearing =calculateBearing(currentLat, currentLon, targetLat, targetLon)val bearingRad = Math.toRadians(bearing)// 使用GROUND坐标系(地面坐标系)val navParam =VirtualStickFlightControlParam().apply{ rollPitchCoordinateSystem = FlightCoordinateSystem.GROUND verticalControlMode = VerticalControlMode.POSITION yawControlMode = YawControlMode.ANGLE rollPitchControlMode = RollPitchControlMode.VELOCITY // 将速度分解为南北和东西分量 pitch = NAVIGATION_SPEED * Math.cos(bearingRad)// 南北分量(5m/s) roll = NAVIGATION_SPEED * Math.sin(bearingRad)// 东西分量(5m/s) yaw = bearing // 让机头指向目标 verticalThrottle = targetAlt }
  • GROUND坐标系是绝对方向,不受无人机朝向影响
  • pitch控制南北,roll控制东西。

虚拟摇杆参数含义https://developer.dji.com/doc/mobile-sdk-tutorial/cn/basic-introduction/basic-concepts/flight-controller.html#虚拟摇杆


第二步:判断何时到达目标点上方附近

持续监测距离

每100ms检查一次当前位置与目标的距离,距离小于预期值ARRIVAL_THRESHOLD,就认为无人机已到达目标点上方附近,停止导航,开始降落:

val navTask =object: Runnable {overridefunrun(){val currentLoc =getAircraftLocation()val remainingDistance =calculateDistance( currentLoc.latitude, currentLoc.longitude, targetLat, targetLon )if(remainingDistance < ARRIVAL_THRESHOLD){// 10米内// 到达目标,停止导航,开始降落 isNavigating =falsestartDynamicAdjustment()}else{// 继续飞行sendNavigationCommand() virtualStickHandler?.postDelayed(this,100)}}}

第三步:精确降落到指定点

无人机虽然到了目标附近(10米内),但有以下问题:

  1. GPS精度有限(±3米),不够精确。
  2. 风力影响,有时候受风的影响,无人机会偏离。
解决方案:视觉识别+位置调整

工作原理:

  1. 无人机摄像头识别地面的特定图像(如二维码、标记点)
  2. 视觉算法计算偏移量(X轴左右,Y轴前后,Z轴距图像距离)
  3. 将偏移量传给无人机
  4. 无人机调整位置,边降落边对准

数据结构:

privatevar xOffset: Double =0.0// X轴偏移(米),正=右,负=左privatevar yOffset: Double =0.0// Y轴偏移(米),正=前,负=后privatevar zDistance: Double =0.0// Z轴距离(米),距降落点高度

外部接口:

// 视觉识别系统调用这些方法更新偏移量(~1Hz)funsetXOffset(offset: Double){ xOffset = offset }funsetYOffset(offset: Double){ yOffset = offset }funsetZDistance(distance: Double){ zDistance = distance }
采用自适应策略,一边降落一遍调整

关键点:
在不同的高度,我们允许的偏移量阈值不同的,高度较高的时候,偏移量就算比较大也可以下降,随着高度降低,我们允许的偏移量阈值会不断缩小(要求越来越向中间对齐)

真实偏移超出偏移量阈值的2倍就停止下降,只进行对齐调整;
真实偏移超出偏移量的1倍,就以0.1m/s的慢速一边降落一边调整;
在偏移量范围内,且高度> 20m,以0.5m/s的速度快速下降;
在偏移量范围内,且高度在5m-20m之间,以0.2m/s的速度下降;
在偏移量范围内,且高度< 5m,以0.2m/s速度下降;

实现:

// 1. 根据高度动态计算允许的误差privatefungetOffsetThreshold(altitude: Double): Double {returnwhen{ altitude >50.0->1.0// 高空:允许1米偏移误差 altitude >20.0->0.5// 中空:允许0.5米偏移误差 altitude >5.0->0.3// 低空:允许0.3米偏移误差else->0.2// 极低空:要求0.2米精度}}// 2. 根据高度和偏移量动态计算下降速度privatefungetDescentSpeed(altitude: Double, xOffset: Double, yOffset: Double): Double {val threshold =getOffsetThreshold(altitude)returnwhen{ xOffset > threshold *2|| yOffset > threshold *2->0.0// 偏移太大:停止下降 xOffset > threshold || yOffset > threshold ->0.1// 偏移较大:慢降 altitude >20.0->0.5// 中高空:快降 altitude >5.0->0.2// 低空:慢降else->0.2// 极低空:极慢降}}

控制逻辑:

大于50m

20-50m

5-20m

小于5m

偏移大于阈值的2倍

偏移大于阈值

偏移小于阈值

获取当前高度和偏移量

高度判断

偏离阈值1m

偏离阈值0.5m

偏离阈值0.3m

偏离阈值0.2m

偏移判断

停止下降,只调整

慢降0.1m/s并且调整

快降并且微调

发送虚拟摇杆指令

高度小于等于0.1m?

着陆完成

第四步:处理避障,降落后停桨。

问题:下视避障会阻止降落

无人机的下视避障系统会将地面识别为障碍物,在接近地面时自动停止下降,我们在高度为5m的时候关闭下视避障,落到地面后调用KeyStartAutoLanding进行停桨。
参考文档:https://sdk-forum.dji.net/hc/zh-cn/articles/14578693771033-如何使用虚拟摇杆降落

低空时关闭下视避障
var downwardObstacleDisabled =false//确保关闭下视避障操作只成功执行一次// 高度<5m时关闭下视避障if(currentAltitude <=5.0&&!downwardObstacleDisabled){ downwardObstacleDisabled =truesetObstacleAvoidanceEnable(false, PerceptionDirection.DOWNWARD)}//关闭下视避障调用方法privatefunsetObstacleAvoidanceEnable(enabled: Boolean,direction: PerceptionDirection){if(direction ==null){ Log.e("Perception","方向参数为空,无法设置避障")return} PerceptionManager.getInstance().setObstacleAvoidanceEnabled(//调用大疆MSDK方法关闭下视避障 enabled, direction,object: CommonCallbacks.CompletionCallback{overridefunonSuccess(){ toastResult?.postValue(DJIToastResult.success("成功设置【${direction.name}】方向的避障为:${if(enabled)"开启"else"关闭"}")) Log.i("Perception","成功设置【${direction.name}】方向的避障为:${if(enabled)"开启"else"关闭"}")}overridefunonFailure(error: IDJIError){ downwardObstacleDisabled =false toastResult?.postValue(DJIToastResult.failed("设置【${direction.name}】方向的避障失败:$error")) Log.e("Perception","设置【${direction.name}】方向的避障失败:$error")}})}

第五步:降落循环完整逻辑

privatefunstartDynamicAdjustment(){ isAdjusting =true virtualStickHandler =Handler(Looper.getMainLooper())val adjustTask =object: Runnable {overridefunrun(){if(!isAdjusting)return// 1. 获取当前状态val currentAltitude = FlightControllerKey.KeyAltitude.create().get(0.0)val currentXOffsetAbs = Math.abs(xOffset)val currentYOffsetAbs = Math.abs(yOffset)// 2. 检查是否着陆if(currentAltitude <=0.1){stopLanding()return}// 3. 低空时关闭下视避障if(currentAltitude <=5.0&&!downwardObstacleDisabled){ downwardObstacleDisabled =truesetObstacleAvoidanceEnable(false, PerceptionDirection.DOWNWARD)}// 4. 计算自适应参数val offsetThreshold =getOffsetThreshold(currentAltitude)val descentSpeed =getDescentSpeed(currentAltitude, currentXOffsetAbs, currentYOffsetAbs)// 5. 构建虚拟摇杆指令val adjustParam =VirtualStickFlightControlParam().apply{ rollPitchCoordinateSystem = FlightCoordinateSystem.BODY verticalControlMode = VerticalControlMode.VELOCITY rollPitchControlMode = RollPitchControlMode.VELOCITY // 水平调整 roll =if(currentXOffsetAbs > offsetThreshold){if(xOffset >0) ADJUSTMENT_SPEED else-ADJUSTMENT_SPEED }else0.0 pitch =if(currentYOffsetAbs > offsetThreshold){if(yOffset >0) ADJUSTMENT_SPEED else-ADJUSTMENT_SPEED }else0.0// 垂直下降 verticalThrottle =-descentSpeed }// 6. 发送指令 VirtualStickManager.getInstance().sendVirtualStickAdvancedParam(adjustParam)// 7. 100ms后再次执行(10Hz) virtualStickHandler?.postDelayed(this,100)}} virtualStickHandler?.post(adjustTask)}

以上,就实现了一整套视觉引导的自适应降落方案

安全注意事项

WARNING

  1. 必须在空旷、安全环境测试
  2. 建议先用DJI模拟器测试
  3. 视觉识别必须持续更新(~1Hz)
  4. 准备好随时手动接管
代码
/** * One-key return to vehicle function (using Virtual Stick instead of FlyTo) * 1. Get aircraft current location * 2. Calculate distance to vehicle using Haversine formula * 3. If distance > 500m, reject with error * 4. Use Virtual Stick to navigate to vehicle location * 5. Switch to precision adjustment when close enough */funreturnToVehicle(callback: CommonCallbacks.CompletionCallback){// Get aircraft current locationval aircraftLocation =getAircraftLocation()if(aircraftLocation ==null||!isLocationValid(aircraftLocation.latitude, aircraftLocation.longitude)){ callback.onFailure(DJICommonError.FACTORY.build("无法获取无人机位置信息"))return}// Vehicle coordinates (hardcoded for now, will be replaced with API later)// TODO: Replace with actual vehicle GPS coordinates from APIval vehicleLatitude =22.579// Example coordinatesval vehicleLongitude =113.941// Example coordinates// Calculate distance using Haversine formulaval distance =calculateDistance( aircraftLocation.latitude, aircraftLocation.longitude, vehicleLatitude, vehicleLongitude )// Distance validation: reject if > 500mif(distance >500){ callback.onFailure(DJICommonError.FACTORY.build("距离过远: ${String.format("%.2f", distance)}m, 超出 500m 限制"))return}// Start virtual stick navigation to vehicle location toastResult?.postValue(DJIToastResult.success("开始飞向车辆位置"))//TODO 这个targetAlt需要后期经过计算算出来。navigateToTarget(vehicleLatitude, vehicleLongitude,100.0, callback)}/** * Navigate to target location using Virtual Stick */privatefunnavigateToTarget( targetLat: Double, targetLon: Double, targetAlt: Double, callback: CommonCallbacks.CompletionCallback ){ VirtualStickManager.getInstance().enableVirtualStick(object: CommonCallbacks.CompletionCallback{overridefunonSuccess(){ VirtualStickManager.getInstance().setVirtualStickAdvancedModeEnabled(true) isNavigating =truestartNavigation(targetLat, targetLon, targetAlt, callback)}overridefunonFailure(error: IDJIError){ callback.onFailure(error)}})}/** * Start navigation loop using Virtual Stick */privatefunstartNavigation( targetLat: Double, targetLon: Double, targetAlt: Double, callback: CommonCallbacks.CompletionCallback ){ virtualStickHandler =Handler(Looper.getMainLooper())val navTask =object: Runnable {overridefunrun(){if(!isNavigating){return}val currentLoc =getAircraftLocation()if(currentLoc ==null){ virtualStickHandler?.postDelayed(this,100)return}// Calculate remaining distanceval remainingDistance =calculateDistance( currentLoc.latitude, currentLoc.longitude, targetLat, targetLon )println("targetLat:"+targetLat+" targetLon:"+targetLon+" currentLoc.latitude:"+currentLoc.latitude+" currentLoc.longitude:"+currentLoc.longitude+" remainingDistance:"+remainingDistance)// Check if arrivedif(remainingDistance < ARRIVAL_THRESHOLD){// Arrived at target, stop navigation isNavigating =false virtualStickHandler?.removeCallbacksAndMessages(null) callback.onSuccess() toastResult?.postValue(DJIToastResult.success("已到达车辆位置,开始精确定位"))//开始调节云台角度,俯仰角为-90°,旋转时间1sstartGimbalAngleRotation(GimbalAngleRotationMode.ABSOLUTE_ANGLE,-90.0,0.0,0.0,1.0)// Start precision adjustmentstartDynamicAdjustment()}else{// Continue navigationval bearing =calculateBearing( currentLoc.latitude, currentLoc.longitude, targetLat, targetLon )val navParam =VirtualStickFlightControlParam().apply{ rollPitchCoordinateSystem = FlightCoordinateSystem.GROUND // Use ground coordinate system verticalControlMode = VerticalControlMode.POSITION yawControlMode = YawControlMode.ANGLE rollPitchControlMode = RollPitchControlMode.VELOCITY // Calculate velocity components based on bearingval bearingRad = Math.toRadians(bearing) pitch = NAVIGATION_SPEED * Math.sin(bearingRad)// North-South component roll = NAVIGATION_SPEED * Math.cos(bearingRad)// East-West component yaw = bearing // Point towards target verticalThrottle = targetAlt // Target altitude} VirtualStickManager.getInstance().sendVirtualStickAdvancedParam(navParam) virtualStickHandler?.postDelayed(this,100)}}} virtualStickHandler?.post(navTask)}funstartGimbalAngleRotation(mode: GimbalAngleRotationMode,pitch: Double,yaw: Double,roll: Double,duration: Double){val rotation =GimbalAngleRotation().apply{setMode(mode)setPitch(pitch)setYaw(yaw)setRoll(roll)setDuration(duration)} KeyManager.getInstance().performAction( KeyTools.createKey(GimbalKey.KeyRotateByAngle), rotation,object: CommonCallbacks.CompletionCallbackWithParam<EmptyMsg>{overridefunonSuccess(result: EmptyMsg?){ toastResult?.postValue(DJIToastResult.success("云台旋转成功")) Log.i("Gimbal","云台旋转成功:yaw:${rotation.yaw},pitch:${rotation.pitch},roll:${rotation.roll}")}overridefunonFailure(error: IDJIError){ toastResult?.postValue(DJIToastResult.failed("云台旋转失败,$error")) Log.e("Gimbal","云台旋转失败,$error")}})}/** * Start dynamic position adjustment loop with adaptive descent * Adjusts position while descending, with stricter requirements at lower altitudes */privatefunstartDynamicAdjustment(){ isAdjusting =true virtualStickHandler =Handler(Looper.getMainLooper())// Send adjustment commands at 10Hzval adjustTask =object: Runnable {overridefunrun(){if(!isAdjusting){return}// TODO 获取脚本检测出的z轴距离val currentAltitude = FlightControllerKey.KeyAltitude.create().get(0.0)val currentXOffsetAbs = Math.abs(xOffset)val currentYOffsetAbs = Math.abs(yOffset)//关闭降落保护,下视避障失效if(currentAltitude <=5&&!downwardObstacleDisabled){ downwardObstacleDisabled =truesetObstacleAvoidanceEnable(false, PerceptionDirection.DOWNWARD)}// 检查是否落地if(currentAltitude <=0.1){stopLanding()return}// Get adaptive thresholds based on altitudeval offsetThreshold =getOffsetThreshold(currentAltitude)val descentSpeed =getDescentSpeed(currentAltitude, currentXOffsetAbs,currentYOffsetAbs)// Log for debuggingprintln("自动调整 - 高度:%.2fm, x偏移:%.2fm,y偏移:%.2fm, 阈值:%.2fm, 下降速度:%.2fm/s".format( currentAltitude, currentXOffsetAbs,currentYOffsetAbs,offsetThreshold, descentSpeed ))// Calculate adjustment parametersval adjustParam =VirtualStickFlightControlParam().apply{ rollPitchCoordinateSystem = FlightCoordinateSystem.BODY verticalControlMode = VerticalControlMode.VELOCITY yawControlMode = YawControlMode.ANGULAR_VELOCITY rollPitchControlMode = RollPitchControlMode.ANGLE // Calculate roll value based on offset// Positive offset (need to move forward) -> positive roll// Negative offset (need to move backward) -> negative rollif(currentXOffsetAbs > offsetThreshold){// Need adjustment roll =if(xOffset >0) ADJUSTMENT_SPEED else-ADJUSTMENT_SPEED }else{// Within threshold, no adjustment needed roll =0.0}if(currentYOffsetAbs > offsetThreshold){ pitch =if(yOffset >0) ADJUSTMENT_SPEED else-ADJUSTMENT_SPEED }else{ pitch =0.0} yaw =0.0 verticalThrottle =-descentSpeed // Descend at adaptive speed} VirtualStickManager.getInstance().sendVirtualStickAdvancedParam(adjustParam) virtualStickHandler?.postDelayed(this,100)}} virtualStickHandler?.post(adjustTask) toastResult?.postValue(DJIToastResult.success("开始动态位置调整"))}/** * Stop landing and cleanup */privatefunstopLanding(){ virtualStickHandler?.removeCallbacksAndMessages(null)//调用KeyStartAutoLanding进行停桨 FlightControllerKey.KeyStartAutoLanding.create().action({ toastResult?.postValue(DJIToastResult.success("桨叶动力关闭")) Log.i("stopLanding","桨叶动力关闭成功")},{ toastResult?.postValue(DJIToastResult.failed("桨叶动力关闭失败")) Log.i("stopLanding","桨叶动力关闭失败!!")})cleanupVirtualStick() toastResult?.postValue(DJIToastResult.success("降落完成"))}/** * Get offset threshold based on current altitude * Higher altitude allows larger offset, lower altitude requires stricter precision */privatefungetOffsetThreshold(altitude: Double): Double {returnwhen{ altitude > HIGH_ALTITUDE ->1.0// High altitude: allow 1m offset altitude > MID_ALTITUDE ->0.5// Mid altitude: allow 0.5m offset altitude > LOW_ALTITUDE ->0.4// Low altitude: allow 0.3m offsetelse->0.3// Very low altitude: require 0.2m precision}}/** * Get descent speed based on current altitude and offset * Larger offset or lower altitude results in slower descent */privatefungetDescentSpeed(altitude: Double, xOffset: Double,yOffset: Double): Double {val threshold =getOffsetThreshold(altitude)returnwhen{ xOffset > threshold *2|| yOffset > threshold *2->0.0// Offset too large: stop descending xOffset > threshold || yOffset > threshold ->0.1// Offset large: slow descent altitude > MID_ALTITUDE ->0.5// Mid-high altitude: fast descent altitude > LOW_ALTITUDE ->0.2// Low altitude: slow descentelse->0.1// Very low altitude: very slow descent}}

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前言 🌟🌟本期讲解关于力扣的几篇题解的详细介绍~~~ 🌈感兴趣的小伙伴看一看小编主页:GGBondlctrl-ZEEKLOG博客 🔥 你的点赞就是小编不断更新的最大动力                                        🎆那么废话不多说直接开整吧~~ 目录 📚️1.前K个高频单词 🚀1.1题目描述 🚀1.2题目解析 🚀1.3代码编写 📚️2.数据流的中位数 🚀2.1题目描述 🚀2.2题目解析 2.2.1第一种思路 2.2.2第二种思路 🚀2.3代码编写 2.3.1第一种代码 2.3.2第二种代码 📚️3.总结 ——前言:关于堆这个数据结构,想必大家多多少少已经了解,并熟悉过了;其中最经典的问题就是使用堆来解决TOPK问题,但是除次之外,堆的构建以及堆来求解中位数,那么不知道大家了解过没有~~~  📚️1.前K个高频单词 🚀1.1题目描述 给定一个单词列表

By Ne0inhk
前端常用算法解析:Bubble Sort,Quick Sort,Merge Sort,Binary Search,DFS,BFS,DP,Dijkstra,Union-Find

前端常用算法解析:Bubble Sort,Quick Sort,Merge Sort,Binary Search,DFS,BFS,DP,Dijkstra,Union-Find

目录 * 一、算法在前端开发中的重要性 * 二、常用算法解析 * 2.1. 排序算法(Bubble Sort,Quick Sort,Merge Sort) * 2.2 二分查找(Binary Search) * 2.3 深度优先搜索(DFS) * 2.4 广度优先搜索(BFS) * 2.5 动态规划(DP) * 2.6 Dijkstra算法 * 2.7 并查集(Union-Find) * 三、总结 一、算法在前端开发中的重要性 算法在前端开发中不仅仅用于面试,更重要的是解决实际问题:优化性能、处理复杂数据、提升用户体验等。 二、常用算法解析 2.

By Ne0inhk
Flutter 三方库 sm_crypto 的鸿蒙化适配指南 - 实现国产密码算法 SM2/SM3/SM4 的端侧加解密、支持数字签名与国密 SSL 安全通信实战

Flutter 三方库 sm_crypto 的鸿蒙化适配指南 - 实现国产密码算法 SM2/SM3/SM4 的端侧加解密、支持数字签名与国密 SSL 安全通信实战

欢迎加入开源鸿蒙跨平台社区:https://openharmonycrossplatform.ZEEKLOG.net Flutter 三方库 sm_crypto 的鸿蒙化适配指南 - 实现国产密码算法 SM2/SM3/SM4 的端侧加解密、支持数字签名与国密 SSL 安全通信实战 前言 在进行针对中国市场的 Flutter for OpenHarmony 企业级或政务级应用开发时,支持国产密码算法(国密)是硬性的合规要求。sm_crypto 是一个功能完备的国密算法 Dart 实现库。它涵盖了非对称加密 SM2、哈希摘要 SM3 以及对称加密 SM4。本文将探讨如何在鸿蒙端利用该库构建符合国家标准的安全加密体系。 一、原原理性解析 / 概念介绍 1.1 基础原理 sm_crypto 严格遵循国家密码管理局发布的 GM/

By Ne0inhk