Motion Control 2009 Part 7 ppt

Motion Control 202 increased with increasing frequency and amplitude, the active body length involved in the swimming increased continually because of the participation of more joints. Nevertheless, all the joints functioned and the active body length remained invariant in the second stage. The two-phase profile demonstrated that the oscillating body length plays an important role in the swimming speed of the AmphiRobot. (a) drive=1 (b) drive=1.5 Terrestrial and Underwater Locomotion Control for a Biomimetic Amphibious Robot Capable of Multimode Motion 203 (c) drive=2 (d) drive=2.5 Fig. 19. A comparison of actual swimming and simulation results Motion Control 204 Fig. 20. The relationship of swimming speed and drive difference 5. Conclusion This chapter has reviewed some of the issues involved in creating a multimode amphibious robot, especially its mechanical design and motion control, in a biomimetic manner. Based on the body structure, motion characteristics of amphibians, two generations of multimode biomimetic amphibious robots, named “AmphiRobot”, have been developed. For terrestrial movements, a geometry based steering method called body-deformation steering has been proposed and optimized, taking advantage of the wheel-like mechanisms attached to the robot. At the same time, a chainlike CPG network responsible for coordinated swimming between multi-joint tail and artificial pectoral fins has been built. The aquatic control parameters mainly involve the length of undulation part, oscillating frequency and amplitude cooperatively regulated by the threshold values of the saturation function for each propelling unit. The real-time online calculation of controlling parameters has been also implemented. Preliminary testing results, both on land and in water, have demonstrated the effectiveness of the proposed control scheme. However, the amphibious locomotion performance of the AmphiRobot is still far behind that of animals in terms of speed and agility, especially in complex unstructured environments. More cooperative efforts from materials, actuators, sensors, control as well as learning aspects will be needed to improve the robot locomotor skills in unstructured and even unknown surroundings. The ongoing and future work will focus on the analysis and optimization of locomotion control for autonomous movements as well as flexible water-land transitions. Hydrodynamic experiments based hybrid mechanical/electrical optimization, of course, is a plus for real-world applications. 6. Acknowledgement The authors would like to thank Prof. Weibing Wang in the Machine and Electricity Engineering College, Shihezi University, for his contribution to mechanical design and fabrication of the AmphiRobot. Terrestrial and Underwater Locomotion Control for a Biomimetic Amphibious Robot Capable of Multimode Motion 205 This work was supported in part by the National Natural Science Foundation of China under Grants 60775053 and 60505015, in part by the Municipal Natural Science Foundation of Beijing under Grant 4082031, in part by the National 863 Program under Grant 2007AA04Z202, and in part by the Beijing Nova Programme (2006A80). 7. References Ayers, J. (2004). Underwater walking, Arthropod Structure and Development, Vol. 33, pp. 347– 360 Bandyopadhyay, P.R. (2004). Guest editorial: biology-inspired science and technology for autonomous underwater vehicles, IEEE J. Ocean. Eng., Vol. 29, No. 3, pp. 542–546 Bandyopadhyay, P.R. (2005). Trends in biorobotic autonomous undersea vehicles, IEEE J. Ocean. Eng., Vol. 30, No. 1, pp. 109–139 Barrett, D.S. (1996). Propulsive efficiency of a flexible hull underwater vehicle, Dissertation for the Doctoral Degree, Cambridge, MA: Massachusetts Institute of Technology Boxerbaum, A.; Werk, P.; Quinn, R. & Vaidyanathan, R. (2005). Design of an autonomous amphibious robot for surf zone operation: Part I mechanical design for multi-mode mobility, Proc. of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1460–1464 Delcomyn, F. (1980). Neural basis for rhythmic behaviour in animals, Science, Vol. 210, pp. 492–498 Ding, R.; Yu, J.; Yang, Q.; Hu, X. & Tan, M. (2009). Platform-level design for a biomimetic amphibious robot, Proc. of IEEE International Conference on Robotics and Biomimetics, Bangkok, Thailand, pp. 977–982 Fish, F.E. & Rohr, J.J. (1999). Review of dolphin hydrodynamics and swimming performance, Technical Report 1801, SPAWARS System Center San Diego, CA Georgiades, C.; Nahon, M. & Buehler, M. (2009). Simulation of an underwater hexapod robot, Ocean Engineering, Vol. 36, pp. 39–47 Greiner, H.; Shectman, A.; Won, C.; Elsley, D. & Beith, P. (1996). Autonomous legged underwater vehicles for near land warfare, Proc. Symp. Autonom. Underwater Vehicle Tech., pp. 41–48 Harkins, R.; Ward, J.; Vaidyanathan, R.; Boxerbaum, A. & Quinn, R. (2005). Design of an autonomous amphibious robot for surf zone operation: Part II - hardware, control implementation and simulation, Proc. of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1465–1470 Healy, P.D. & Bishop, B.E. (2009). Sea-dragon: an amphibious robot for operation in the littorals, Proc. of 41st Southeastern Symp. on System Theory, University of tennessee Space Institute, Tullahome, TN, USA, pp. 266–270 Ijspeert, A.J.; Crespi, A. & Cabelguen, J M. (2005). Simulation and robotic studies of salamander locomotion: applying neurobiological principles to the control of locomotion in robots, Neuroinformatics, Vol. 3, pp. 171–196 Ijspeert, A.J.; Crespi, A.; Ryczko, D. & Cabelguen, J M. (2007). From swimming to walking with a salamander robot driven by a spinal cord model, Science, Vol. 315, No. 5817, pp. 1416–1420 Ijspeert, A.J. (2008). Central pattern generators for locomotion in animals and robots: a review, Neural Networks, Vol. 21, No. 4, pp. 642–653 Motion Control 206 Kemp, M.; Hobson, B. & Long, J. (2005). Madeleine: an agile auv propelled by flexible fins, Proc. of the 14th International Symposium on Unmanned Untethered Submersible Technology (UUST), pp. 1–6 Lauder, G.V.; Anderson, E.J.; Tangorra, T.J. & Madden, P.G.A. (2007a). Fish biorobotics: kinematics and hydrodynamics of self-propulsion, The Journal of Experimental Biology, Vol. 210, pp. 2767–2780 Lauder, G.V. & Madden, P.G.A. (2007b). Fish locomotion: kinematics and hydrodynamics of flexible foil-like fins, Exp. Fluids, Vol. 43, pp. 641–653 Prahacs, C.; Saunders, A.; Smith, M.; McMordie, D. & Buehler, M. (2005). Towards legged amphibious mobile robotics, J. Eng. Design and Innovation (online), vol. 1, part. 01P3, Available: www.cden.ca/JEDI/index.html Sfakiotakis, M.; Lane, D.M. & Davies, J.B.C. (1999). Review of fish swimming modes for aquatic locomotion, IEEE J. Oceanic Eng., Vol. 24, No. 2, pp. 237–252 Yamada, H.; Chigisaki, S.; Mori, M.; Takita, K.; Ogami, K. & Hirose, S. (2005). Development of amphibious snake-like robot ACM-R5, Proc. of 36th Int. Symposium on Robotics, pp. 433–440 Yang, Q.; Yu, J.; Tan, M. & Wang, S. (2007). Amphibious biomimetic robots: a review, Robot, Vol. 29, No. 6, pp. 601–608 Yu, J.; Tan, M.; Wang, S. & Chen, E. (2004). Development of a biomimetic robotic fish and its control algorithm, IEEE Trans. Syst., Man, Cybern. B, Cybern., Vol. 34, No. 4, pp. 1798–1810 Yu, J.; Hu, Y.; Fan, R.; Wang, L. & Huo, J. (2007). Mechanical design and motion control of a biomimetic robotic dolphin, Advanced Robotics, Vol. 21, No. 3–4, pp. 499–513 Wang, L.; Sun, L.; Chen, D.; Zhang, D. & Meng, Q. (2005). A bionic crab-like robot prototype, Journal of Harbin Engineering University, Vol. 26, No. 5, pp. 591–595 10 Autonomous Underwater Vehicle Motion Control during Investigation of Bottom Objects and Hard-to-Reach Areas Alexander Inzartsev, Lev Kiselyov, Andrey Medvedev and Alexander Pavin Institute of Marine Technology Problems (IMTP FEB RAS) Far East Branch of the Russian Academy of Sciences Russia 1. Introduction Modern Autonomous Underwater Vehicles (AUVs) can solve different tasks on sea bosom research, objects search and investigation on the seabed, mapping, water area protection, and environment monitoring. In order to solve problems of bottom objects survey AUV has to move among the obstacles in a small distance from the seabed. Such motion is connected with active manoeuvring, changes in speed and direction of the movement, switch and adaptive correction of modes and control parameters. This can be exemplified by using AUV for geologic exploration and raw materials reserves estimation in the area of seamounts, which are guyots with rugged topography. Such problems arise during vehicle manoeuvring near artificial underwater point or extended objects (for example, dock stations or underwater communications). The problems of ocean physical fields’ survey are of a particular interest. These are the problems of bathymetry and seabed mapping as well as signature areas of search objects. To perform these tasks AUV must be equipped with the systems that can define the positions of the vehicle body against the obstacles and search objects. As a rule, acoustic distance-measuring systems (multibeam and scanning sonars, and also groups of sonars with the fixed directional diagram) and other vision systems are used for these purposes. AUV path planning is carried out with the use of current sensory data due to the lack of a priori information. On the basis of measured distances the current environment model and the position of the vehicle are defined. Then taking into account vehicle dynamic features the direction of probable movement and usable motion modes are evaluated. At each control phase a motion replanning is carried out taking into account new data received from sensors and changed surrounding. The paper presents the results of research and working outs based on the many years of experience of the Institute of Marine Technology Problems (IMTP) FEB RAS (Ageev et al., 2005). It also gives examples of realization of the offered solutions in the structure and algorithms of motion control of certain autonomous underwater vehicles-robots. Motion Control 208 2. Control system peculiarities of AUV capable to work at severe environment The use of AUV to perform different operations under conditions of difficult informative uncertain or extreme surrounding requires a developed complex of positioning, control, and computer vision systems onboard the vehicle. In the overall structure of control system one can mark such basic systems providing AUV functioning as an equipment carrier, and information and searching functions. The basis of control system is a local area network composed of several computers. It provides motion control and emergency and search functions. To organize AUV’s local area network high speed channels (Ethernet) and quite slow exchange serial channels are used. To form the control navigation and sensors’ data are used. Emergency sensors are used for AUV safety. Remote change of AUV mission can be carried out with the help of acoustic link. Positioning system plays an important role. Positioning accuracy is acquired by using on-board autonomous navigation system including inertial positioning system, angular and position measuring devices, and acoustic Doppler log. An accumulating dead-reckoning error can be decreased by means of integration of hydroacoustic and stand-alone data by operating AUV with hydroacoustic navigation facilities with long or ultra-short base. Search systems incorporated computer vision systems differ on physical principles and methods of data acquisition. Acoustic systems include high-frequency and low-frequency side-scan and sector-scan sonars as well as subbottom profiler. Current-conducting objects can be found with the use of electromagnetic locator (EML). A video system carries out imaging and object recognition. It includes photo and video cameras. The information from sensors and measuring systems are usually stored for the following mapping of researched area (ecological, geophysical, etc.) If necessary, this information can be used in real time, for example, for contouring the areas with abnormal characteristics of measured fields. System architecture of programmed control has hierarchic three-level organization (strategic, tactic and executive levels). Program-task (mission) for the vehicle is programmed on the highest level and in general it contains the description of desired motion path and operation modes of onboard equipment. Tactic level contains a set of vehicle behavior models (function library) and a scheduler that coordinates their work. The lowest level carries out tactical commands. To do this it contains a set of servocontrollers. Control algorithms providing “reflex” motion among the obstacles work on the lowest level. The propulsion system is used for spatial motion, positioning, and obstacle avoiding. It provides free motion modes (motion in wide speed range, hovering, and free trim motion). There are stern and bow propulsion sections. Control forces and moments are created with the help of four stern mid-flight and several stern and fore lateral thrusting propulsions. Multi-beam echoranging system (ERS) with the range up to 75 meters is used for working out corresponding controls and obstacles detection. ERS sonars are oriented on the front aspect under different angles to vehicle fore-and-aft axis (forward, down, sideway, up). 3. Motion modes and AUV dynamics peculiarities Trajectories of arbitrary forms are required for bottom objects survey, constructions inspection, docking with mooring facilities or homing beacons. Not only basic motion modes but more difficult modes of dynamic positioning at variable speed and circular change of thrust vector direction (start-stop, reverse, transversal, etc.) must be performed. Among typical practical tasks of this class are: Autonomous Underwater Vehicle Motion Control during Investigation of Bottom Objects and Hard-to-Reach Areas 209 • maneuvering in specified area near the target at variable speed and heading correction, pointing to the target (signal source), approaching to the target and point positioning, • lengthy objects search and survey, • path selection in the rugged bottom relief. In many cases the said missions are interconnected and can correspond to different phases of a particular vehicle mission. So we shall consider them as components of single scenery for rather complex missions’ performance. Fig. 1. A system of coordinates and flow pattern of force in trimetric projection Let’s equate the model of AUV spatial motion as (fig. 1): 0 11 22 33 sin cos cos cos sin , cos cos cos , sin , , cos cos , sin , sin cos . ,,, xx x y z yy x y ctrl zz z ctrl yyy Tx Ty Tz xy z mRP T T T mRP T T JMM M JMM X Y Z mM mM mM I υ ϑαβαβ υϑ ϑ α α ψψ ϕ υϑϕυ υϑυ υϕϑυ λλ λ =− + ⋅ + ⋅ ⋅ − ⋅ − ⋅ =+⋅ +⋅ +⋅ =+⋅ + =+ =⋅ ⋅ + =⋅ + =⋅ ⋅ + =+ =+ =+        55 66 ,, yyy zzz III λ λ =+ =+ (1) where λ 11 , λ 22 , λ 33 , λ 55 , λ 66 – added masses and liquid inertia moment, T x1 , T y1 , T z1 , M y ctrl , M z ctrl – projection of control forces and moments in a system of coordinates dependent on the vehicle, υ - speed against the flow, φ, ψ – heading and vehicle pitch correspondingly, ϑ , χ – angles of ascent and motion swing, R x , R y , R z , M y , M z – hydrodynamic forces and moments, M 0 – moment of stability, υ Tx , υ Ty , υ Tz – current velocity vector components which Motion Control 210 have constant, variable or random character, P – variable buoyancy depending, in particular, on the depth of the vehicle descent. According to the general formulation area survey is performed with the help of maneuvering piecewise-constant speed and path program near the target (object) and start- stop control mode at point dynamic positioning or along the contour. Horizontal motion area (X, Z) can be defined by one of the following methods: • coordinates of the target point {X T , Z T }, local area radius r T and distance to the target d T , distance d B to the signal source (transponder) and bearings ϑ B , • optional close circuit g(X,Z)=0, against which the vehicle displacement d i is defined in directions dependent of the vehicle, • linear zone |aX+bZ+c| ≤ Δ l width Δ l against extended object and relative linear {ΔX l ,ΔZ l } and angular Δϕ l vehicle motions. Control responses created by the stern and bow propulsions in the trimetric projection connected with the vehicle are given by (Ageev et al., 2005; Kiselev & Medvedev, 2009): ()cos, ()sin , ( ) sin , ( )( sin cos ) , ()(sincos) , x SUSRSBSL S ySUSB BHyBV S zSRSL BVzBH ctrl S z SU SB BV TB y BV TB ctrl S ySRSLTS TS BHTBz BHTB TS TS TTTTT TTT TTT TTT TTT M T Tx y Tx TdTx MTTx z TxTdTx d δ δ δ δδ δδ =+++⋅ =−⋅+=+ =−⋅ +=+ =− + +⋅=⋅+⋅ =− + +⋅=⋅+⋅ = max max max max ( sin cos ) sin , ,. TS TS TS TS SB TT B S SB B S xy xyctg UU TT sat TT sat TT δδδ δ ⋅+⋅ =+⋅ ⎛⎞ ⎛⎞ =⋅ =⋅ ⎜⎟ ⎜⎟ ⎝⎠ ⎝⎠ (2) where Т SU , Т SB – vertical channel stern mid-flight propulsions thrusts (upper and bottom correspondingly), Т SR , Т SL - horizontal channel stern mid-flight propulsions thrusts (right and left correspondingly), Т BH , Т BV - horizontal and vertical bow maneuvering thrusts, х TS , у TS , δ - coordinates and pitch angle of stern mid-flight propulsions, х TB - axial coordinate of bow maneuvering propulsion, U S T , U B T - control functions for stern and bow propulsion sections. As is clear from set of equations one and the same control responses can be created by means of applying different work patterns of stern and bow propulsions. A practical application has the following modes: • cruising motion; • low speed motion. The first mode is characterized by the fact that vehicle spatial motion is carried out by means of changing of attack angle with the help of variables T x , M Y CTRL , M Z CTRL . At the same time only stern mid-flight propulsions form the mentioned forces and moments. This mode is used for vehicle control only at cruising speed. [...]... of the task performing is given below 7. 1 Path control with field isolines search and tracking Isoline motion joins the tasks of field mapping and motion control along isoline paths, motion along which contains constant value Program algorithm in this case must contain conditions controlling ordered transfer from one curve to another as well as angular motion control law that displays isoline flection... 222 Motion Control provide decreasing of dm upon the average, keeping dm = 0 and vehicle angle orientation on target bearing 7 AUV motion control during investigation of ocean physical fields The tasks of AUV motion control are usually connected with bottom survey, object search, and inspection in near-bottom space as well as physical fields’ measurements (Ageev et al., 2005; Kiselev & Medvedev, 2009) ... several possible control methods They differ by the logic of program algorithm and by system dynamics in performing complex spatial motions 4 Motion control in the rugged bottom relief AUV usage for seabed layer survey is connected with the organization of equidistant motion (motion at equally distance from the seabed) and bypassing or bending around the obstacles Equidistant motion control assumes... ISBN 978 -953 -76 19-49 -7, open access: www.intechweb.org Kiselev, L.; Inzartsev, A.; Matviyenko, Yu & Rylov, N (20 07) Current issues of navigation and control in autonomous underwater vehicle development, Proc of International Conference on Subsea Technologies SubSeaTech’20 07, June 25-28, St.Petersburg, Russia, ISBN 5-88303-409-8 Kiselyov, L & Medvedev A (2009) Typology Models of Dynamic AUV Spatial Motion, ... programmed course if another motion parameters are known Let’s consider the task of motion control during search and tracking of given isoline ξ = ξ0, considering that control vector consists of two components – one of them for position control, the other one for orientation control Autonomous Underwater Vehicle Motion Control during Investigation of Bottom Objects and Hard-to-Reach Areas 225 Let’s define... the “peak” and starts backward motion This motion algorithm allows avoiding getting into the “gorges” if their width is compared to the ERS radius of action The example of AUV upward motion on the slope with rather rugged relief is depicted in fig 4 Fig 4 Rugged relief motion The whole motion path consists of several areas Each area has its own motion mode AUV preset motion height over the bottom is... is extended It is crucial to develop control systems with integrated processing of search and navigation information Control and navigation systems developed Autonomous Underwater Vehicle Motion Control during Investigation of Bottom Objects and Hard-to-Reach Areas 2 27 by IMTP FEB RAS enable performance of many search-and-survey operations in the sea Navigation -control facilities are the basis for...Autonomous Underwater Vehicle Motion Control during Investigation of Bottom Objects and Hard-to-Reach Areas 211 In the second mode all propulsion sections are used to form vehicle motion, and control is performed according to five degrees of freedom with the help of variables Tx, TY, TZ, MYCTRL, MZCTRL This mode is used for vehicle control at low speed and during hovering Complex AUV motions are carried out... distance D and direction ϕt Autonomous Underwater Vehicle Motion Control during Investigation of Bottom Objects and Hard-to-Reach Areas a) 221 b) Fig 9 The results of modeling, a) – motion path and parameters at constant current, b) motion path and parameters at variable current (time in seconds) The use of fuzzy regulator brings to implicit switching of motion modes, so switching zonal boundaries (fig 8)... additional energy consumption for motion performing One more peculiarity is incomplete, unreliable, fuzzy information about the bottom configuration It leads to the suitability of construction of hybrid control structure with fuzzy-logic elements (Ageev et al., 2000; Kiselev & Medvedev, 2009) Let us cite as an example the results of motion modeling in vertical plane for such typical control modes as obstacle . Locomotion Control for a Biomimetic Amphibious Robot Capable of Multimode Motion 205 This work was supported in part by the National Natural Science Foundation of China under Grants 6 077 5053. (2007a). Fish biorobotics: kinematics and hydrodynamics of self-propulsion, The Journal of Experimental Biology, Vol. 210, pp. 276 7– 278 0 Lauder, G.V. & Madden, P.G.A. (2007b). Fish locomotion:. offered solutions in the structure and algorithms of motion control of certain autonomous underwater vehicles-robots. Motion Control 208 2. Control system peculiarities of AUV capable to work