Navigation Functionalities for an Autonomous UAV Helicopter

More documents

Recommendations

Info

90 APPENDIX A. From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle North [m] 20 0 −20 −40 −60 −80 −100 −120 −140 −160 −180 Closed loop YACS on the roll channel Start End Flight tested Target −20 0 20 40 60 80 East [m] North [m] 20 0 −20 −40 −60 −80 −100 −120 −140 −160 −180 Open loop YACS Start End Flight tested Target −20 0 20 40 60 80 East [m] Figure 7: Comparison of path tracking performances using two different roll controller. The flight-test where performed at 36 km/h constant velocity for both paths. are calculated as follows: Vmax1(s) = � Rxy(s)gφmax Vmax2(s) = ω 2 maxRxy(s) The minimum between Vmax1(s), Vmax2(s) and Vtar(s) is taken as target velocity by the path controller described in the next subsection. Thus, the calculated velocity is compatible with the curvature radius of the path. 5.2 Path Controller Usually the control system for a helicopter consists of an inner loop, which is responsible for stabilizing the attitude, and the outer loop, which controls the position and velocity. In our system we use the Yamaha Attitude Control System (YACS) provided with the RMAX helicopter for the attitude control. For the outer loop we use four decoupled PID controllers. Their outputs are used as input to the YACS system. In (3) the control approach for the RMAX has been described and experimental results provided. In this section, we present results of a modified controller, which uses an additional feedback loop on 21 th Bristol UAV Systems Conference — April 2006 the roll channel. Several experiments were done closing the roll angle loop around the YACS in order to test if it is feasible to improve path tracking precision without a complete redesign of the attitude controller. The modified controller has been flight-tested on the RMAX helicopter at a constant velocity of 36km/h on a path with changing curvature. Such a path is typically used to navigate in areas with obstacles. The results are shown in Fig. 7 where the same path was tested both with the roll loop closed around the YACS, and without. Note, that at the beginning of the path when the dynamic response of the controller is more important because of the changing curvature, the control with additional feedback loop over the roll channel performs much better than the other one. The error for the closed loop controller in this part is below 1 meter, while for the other is around 6 meters. The results obtained during flight-tests show that the loop on the roll channel reduces the path tracking error, what makes the controller more suitable for obstacle-cluttered environments. The following section describes interaction between the path following control mode with a Task Procedure responsible for executing a planned path.
A.2. PAPER II 91 From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle 6 Path Execution Mechanism The key element of the framework is the path execution mechanism. It allows for seemless integration of hard real-time componets (e.g. the path following controller) with inherently non real-time deliberative services (e.g. the path planners). The execution of the path provided by the path planner is divided into two parts, namely the Task Procedure and the Path Following controller. The standard path execution scheme in our architecture for static operational environments is depicted in Fig. 8 (key functional componets involved in navigation are drawn in black). A UAV mission is specified via a Task GIS Service * *- CORBA-based Real-time communication channel Other Modes Hovering Mode Path Planner Service * Plan 2 1 Task Procedures * 4 End points, Constraints Helicopter Server * CORBA HCSM Interpreter (C-API) 3 HCSM Interpreter Path Following Mode Other Services * DRC PFC Communication Handling Hardware Handling Figure 8: Path execution mechanism Distributed System Procedure in the reactive layer of our architecture, (perhaps after calling a task-based planner). For the purpose of this paper, a TP can be viewed as an augmented state machine. For the case of flying to a waypoint, an instance of a navigation TP is created. First it calls the path planner service (step 1) with the following parameters: initial position, goal position, desired velocity and additional constraints. If successful, the path planner (step 2) generates a segmented path which is represented as a set of cubic 21 th Bristol UAV Systems Conference — April 2006 polynomial curves. Each segment is defined by start and end points, start and end directions, target velocity and end velocity. The TP sends the first segment (step 3) of the path via the control system interface and waits for the Request Segment event. It is generated by the HCSM responsible for the path execution as soon as the path following (PF) controller output is fed with a path segment. When a Request Segment event arrives (step 4) the TP sends the next segment data to the HCSM which coordinates the path execution. This procedure is repeated (step 3-4) until the last segment is executed. However, because the high-level system is not implemented in hard real-time it may happen that the next segment does not arrive at the Control Kernel on time. In this case, the controller has a timeout limit after which it goes into safety braking mode in order to stop and hover at the end of the current segment. The timeout is determined by a velocity profile, current position and current velocity. ∆t1total ∆t2total t0 t1 ∆t1timeout t2 ∆t2timeout TP 2 PF t 1 – segment 1; 2 – Request segment 3 – segment 2 1 3 tstart1 to1 tarrive1 tstart2 t to2 tarrive2 braking flying segment 1 braking flying segment 2 Figure 9: Execution timeline for trajectory consisting of 2 segments Fig. 9 depicts a timeline plot of the execution of a trajectory (2 segments). At time t0, a TP sends the first segment of the path to the PF controller and waits for a Request segment event which arrives immediately (t1) after the helicopter starts to fly (tstart1). Typical time values for receiving a Request segment event (t1 − t0) are well below 200ms. Time to1 is the timeout
Page 1:
Linköping Studies in Science and T
Page 5:
Acknowledgements This work would ha
Page 9 and 10:
Contents 1 Introduction 1 2 Overvie
Page 11 and 12:
Chapter 1 Introduction An Unmanned
Page 13 and 14:
of the environment in order to avoi
Page 15 and 16:
Chapter 2 Overview This chapter pre
Page 17 and 18:
2.1. UAV SOFTWARE ARCHITECTURE 7 wh
Page 19 and 20:
2.2. THE UAV HELICOPTER PLATFORM 9
Page 21 and 22:
2.2. THE UAV HELICOPTER PLATFORM 11
Page 23 and 24:
Chapter 3 Simulation 3.1 Introducti
Page 25 and 26:
3.2. HARDWARE-IN-THE-LOOP SIMULATIO
Page 27 and 28:
3.3. REFERENCE FRAMES 17 3.3 Refere
Page 29 and 30:
3.4. THE AUGMENTED RMAX DYNAMIC MOD
Page 31 and 32:
3.4. THE AUGMENTED RMAX DYNAMIC MOD
Page 33 and 34:
3.5. SIMULATION RESULTS 23 3.5 Simu
Page 35 and 36:
3.5. SIMULATION RESULTS 25 Figure 3
Page 37 and 38:
3.5. SIMULATION RESULTS 27 Figure 3
Page 39 and 40:
Chapter 4 Path Following Control Mo
Page 41 and 42:
4.2. TRAJECTORY GENERATOR 31 Figure
Page 43 and 44:
4.2. TRAJECTORY GENERATOR 33 Fig. 4
Page 45 and 46:
4.2. TRAJECTORY GENERATOR 35 be use
Page 47 and 48:
4.2. TRAJECTORY GENERATOR 37 4.2.3
Page 49 and 50: 4.2. TRAJECTORY GENERATOR 39 radius
Page 51 and 52: 4.2. TRAJECTORY GENERATOR 41 Calcul
Page 53 and 54: 4.2. TRAJECTORY GENERATOR 43 Figure
Page 55 and 56: 4.2. TRAJECTORY GENERATOR 45 by the
Page 57 and 58: 4.2. TRAJECTORY GENERATOR 47 Figure
Page 59 and 60: 4.3. OUTER LOOP CONTROL EQUATIONS 4
Page 61 and 62: 4.4. EXPERIMENTAL RESULTS 51 Up [m]
Page 63 and 64: 4.5. CONCLUSIONS 53 1 + s 1 C(s) =
Page 65 and 66: 4.5. CONCLUSIONS 55 Vel [m/s] 20 18
Page 67 and 68: Chapter 5 Sensor fusion for vision
Page 69 and 70: composed of three accelerometers an
Page 71 and 72: 5.1. FILTER ARCHITECTURE 61 filter
Page 73 and 74: 5.1. FILTER ARCHITECTURE 63 north,
Page 75 and 76: 5.2. EXPERIMENTAL RESULTS 65 Figure
Page 77 and 78: 5.2. EXPERIMENTAL RESULTS 67 Figure
Page 79 and 80: 5.2. EXPERIMENTAL RESULTS 69 by the
Page 81 and 82: 5.3. CONCLUSION 71 vision system st
Page 83 and 84: BIBLIOGRAPHY 73 [9] E. Frazzoli. Ro
Page 85 and 86: Appendix A 75
Page 87 and 88: A.1. PAPER I 77 is a three-dimensio
Page 89 and 90: A.1. PAPER I 79 The reference point
Page 91 and 92: A.1. PAPER I 81 Path Av Err Max Err
Page 93 and 94: A.2. PAPER II 83 From Motion Planni
Page 99: A.2. PAPER II 89 From Motion Planni
Page 107 and 108: A.3. PAPER III 97 A.3 Paper III Aut
Page 109 and 110: A.3. PAPER III 99 the projection of
Page 111 and 112: A.3. PAPER III 101 yes Tbo > Tlim2
Page 113 and 114: A.3. PAPER III 103 immediately afte
Page 115 and 116: A.3. PAPER III 105 altitude [m] 20
Page 117: A.3. PAPER III 107 Fig. 10. Flight
Page 121 and 122: Department of Computer and Informat
Page 123 and 124: No 598 Rego Granlund: C 3 Fire - A
Page 125 and 126: No 1024 Aleksandra Tešanovic: Towa
show all

Navigation Functionalities for an Autonomous UAV Helicopter

Create successful ePaper yourself

Delete template?

Save as template?