Amphibian Robot

IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 17, NO. 5, OCTOBER 2012 847

On a Bio-inspired Amphibious Robot Capableof Multimodal Motion

Junzhi Yu, Rui Ding, Qinghai Yang, Min Tan, Weibing Wang, and Jianwei Zhang

Abstract—This paper addresses the system design and locomo-tion control for a versatile amphibious robot, AmphiRobot-II, in-spired by various amphibian principles in the animal kingdom. Interms of the propulsion features of existing amphibians, a novel hy-brid propulsive mechanism coupled with wheel-propeller-fin move-ments is proposed that integrates fish- or dolphin-like swimmingand wheel-based crawling. The robot is able not only to implementflexible wheel-based movements on land, but also to perform steadyand efficient fish- or dolphin-like swimming under water and canfurther switch between these two patterns via a specialized swiveldevice. To achieve multimodal motions, a body deformation steer-ing approach is proposed for the turning locomotion on land withminimum turning radius obtained accordingly. A central patterngenerator inspired underwater locomotion control is also imple-mented and tested on the physical robot. Based on the aforemen-tioned design, the AmphiRobot-II prototype has been built andhas successfully demonstrated to confirm the effectiveness of thehybrid propulsive scheme and the amphibious control approaches.

Index Terms—Amphibious robot, bio-inspired robot, mechani-cal design, motion control, multimodal motion.

I. INTRODUCTION

B IO-INSPIRED mechatronics is emerging as a multidisci-plinary subject focusing on learning and mimicking bi-

ologic characteristics and functions and then reproducing andeven outperforming these characteristics [1]– [3]. It has drawngreat interest in the area of robotics related to biological func-tions, mechatronics, control technology, computational intelli-gence, etc. One of the crucial features that an amphibious robotshould exhibit is multiple mobility suitable for diverse workingconditions. A primary motivation is that most existing robots

Manuscript received July 12, 2010; revised November 22, 2010; acceptedFebruary 12, 2011. Date of publication May 10, 2011; date of current versionAugust 17, 2012. Recommended by Technical Editor G. Morel. This work wassupported in part by the National Science Foundation of China under Grant60725309 and Grant 61075102, in part by the Beijing Natural Science Foun-dation under Grant 4082031 and Grant 4102063, in part by the Nation 863Program under Grant 2007AA04Z202, and in part by the Alexander von Hum-boldt Foundation of Germany.

J. Yu, R. Ding, and M. Tan are with the State Key Laboratory of Man-agement and Control for Complex Systems, Institute of Automation, ChineseAcademy of Sciences, Beijing 100190, China (e-mail: [email protected];[email protected]; [email protected]).

Q. Yang is with the Research Institute of Petroleum Exploration and Devel-opment, Petrochina, Beijing 100083, China (e-mail: [email protected]).

W. Wang is with the Machine and Electricity Engineering College, ShiheziUniversity, Shihezi 832003, China (e-mail: [email protected]).

J. Zhang is with the Department of Informatics, University of Hamburg,22527 Hamburg, Germany (e-mail: [email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TMECH.2011.2132732

can only operate in a specific environment. For example, theground-based robots are unable to work in water due to lack ofa working aquatic propulsor and necessary waterproof device,while the predominant underwater robots lack sufficient terres-trial motion ability as they will undergo larger friction on land.As a consequence, inspired by amphibians such as the crab, tor-toise, frog, crocodile, penguin, and newt in nature, researchersshow an intense desire to design and develop autonomous, self-contained amphibious robots not only suitable for the land aswell as turbulent ocean surf zones, but also adaptable to compli-cated aquatic circumstances [4]–[6]. The development of fullyautonomous amphibious robots has great theoretical value in ex-ploring biological design principles as well as broad applicationprospects related to underwater environment exploration anddata gathering with minimum disturbance to the surroundinglife-forms.

The existing amphibious robots, in general, fall into two cate-gories in terms of the applied locomotor propulsor, i.e., leg-likeamphibious robots and snake-like ones. The former represen-tatively involves the cockroach-inspired wheel-leg propellersnamed Whegs [7], a lobster-like robot for the purpose of neu-ral control [8], the crab-like autonomous legged underwatervehicles [9], etc. Attempts have also been made to simulate an-guilliform swimming by sea snakes and lampreys in water andlateral undulatory locomotion by snakes on land. Such snakerobots with special attention to waterproof protection includethe modularly designed ACM-R5 by the Tokyo Institute ofTechnology [10], and the AmphiBot developed by the SwissFederal Institute of Technology [11]. As two distinct locomo-tor forms, the leg- and snake-like propulsors have their owncharacteristics suitable for varying applications. Conventionallegged robots should touch the land and capitalize on mutualfriction for forward motion, which is primarily applicable tomovements on the land or the sea bottom. By contrast, commonsnake robots only perform planar crawling motions, where 3-Dswimming can be accomplished only when specific modifica-tions are made to the propulsive structure. Furthermore, unlikelegged robots that may even perform well in rugged terrain,snake robots might get partly or completely stuck in soft wet-land that has an adverse impact on the ongoing locomotion. Onthe other hand, leg-like propulsors usually pose a great challengeto maintenance overhaul owing to the complicated mechanicalconfiguration. Then again, slender snake robots are easily man-ufactured as a modular structure. So there is a serious need todevelop a versatile amphibious robot affording a plurality ofprimary locomotion means.

The aim of this paper, on the basis of our previous researchon the amphibious robot [12], [13], is to provide an updatedversion for more versatile and excellent locomotor performance

1083-4435/$26.00 © 2011 IEEE

848 IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 17, NO. 5, OCTOBER 2012

both on land and in water. The robot’s key features reside in:1) modularly designed fish-like propelling units according tothe philosophy of modularization and morphological mimicryare utilized to achieve fast and flexible swimming; 2) the incor-poration of a pair of composite wheel-propeller-fin mechanismsinto the robot “AmphiRobot-II” ensures a good performance ofboth terrestrial and underwater locomotion; 3) a specially de-signed swivel mechanism allows a smooth transition betweenthe fish- and dolphin-like modes; and 4) a body-deformation-based steering approach is proposed for the terrestrial motions,whereas a central pattern generator (CPG)-based locomotioncontrol method is used for swimming motions. Furthermore, allmechanical designs and control methods are verified by exten-sive on-site experiments. According to the authors’ knowledge,the AmphiRobot-II may be the only miniature amphibious pro-totype capable of fish-like swimming, dolphin-like swimming,and a propeller mode for propulsion under water.

The rest of the paper is organized as follows. An over-all description of the updated mechanical design scheme forthe AmphiRobot-II together with its implementation is pro-vided in Section II. The body-deformation-based steering ap-proach is proposed for terrestrial locomotion in Section III.The CPG-centered underwater locomotion control is detailed inSection IV. Experiments and analysis performed are presentedin Section V. Finally, conclusions and future work are summa-rized in Section VI.

II. UPDATED MECHANICAL DESIGN AND REALIZATION

A. Updated Scheme

Our previous work on amphibious locomotion focused onproof-of-concept propulsive mechanisms and resulted in a robot“AmphiRobot-I” [12], which partly possesses scheduled terres-trial and/or aquatic motions. However, there exist many openproblems that degrade the propulsive performance to someextent.

1) Compared to the biological counterpart, the oversimpli-fication of the AmphiRobot-I regarding shape generatesadverse hydrodynamic drag when swimming in water.

2) The clearance between the adjacent fish-like propellingunits that will be filled with fluids is somewhat big, whichwill slow the forward speed.

3) Due to the insufficient torque produced by the adopted dcmotor, the devised wheel paddle mounted on the foreheadis unable to drive the robot quickly on land.

4) The overemphasized modular concept leads to the under-estimation of the gross mass of the last propelling unit,including the caudal peduncle and toothed synchro belt,accompanied by insufficient buoyancy.

Taking account of these open problems, we proposed an up-dated concept design of the AmphiRobot-II as shown in Fig. 1,which is capable of effective multimodal gaits both on land andin water. The oscillations of a chain of fish-like propelling unitsin conjunction with a composite peduncle mechanism and a cau-dal fin perform carangiform swimming. The number of modularpropelling units can be appended or detached depending on thedemand. Notice that only the last third of the body length of a

Fig. 1. Mechanism design of AmphiRobot-II. (a) Concept design. (b) Proto-type of the amphibious robot in field test.

carangiform swimmer participates in undulations in the contextof fish swimming [14]. As the most unique point of this robot,it has a joint with roll-axis at the neck (i.e., a swivel mecha-nism), which enables the robot to change the axis of posteriorjoints between yaw axis and pitch axis. Thus, using this joint,the robot can perform both fish-like and dolphin-like swimming.Additionally, with the multipurpose flipper as an antetype, a pairof composite wheel-propeller-fin mechanisms driven by high-torque motors is introduced and fabricated. It acts as the wheelfor crawling on land and as the pectoral fin for balance andpropulsion in water. Moreover, some engineering issues relatedto buoyancy design, component layout, and waterproof sealingare further coped with effectively.

B. Morphological Modification

During swimming the complex hydrodynamic interaction stillremains an open problem, where a well-streamlined body playsan important part in vortices-based control and drag reduction.In terms of hydrodynamics, form drag caused by the distor-tion of flow around solid bodies is determined by their shapes.Therefore, we have effected some modifications.

1) To reduce or eliminate added mass effect, the clear-ance between neighboring propelling units is filled withlightweight convexo-concave cork that can reduce thefore-and-aft space, as shown in Fig. 2(a). Incidentally,an interspace of 3 mm is held at the current version.

2) As illustrated in Fig. 2(b), the posterior clearance betweenthe last module and the peduncle is crammed with a foamstructure with an infill of aluminium sheathing, whichcan fill up the deficiency of buoyancy and generate addedpropulsion due to interaction with expelled fluid.

3) Instead of the flat profile of the AmphiRobot-I, the sidepanels of the fish-like propelling unit made of transpar-ent perspex are changed to convex camber so as to offer

YU et al.: ON A BIO-INSPIRED AMPHIBIOUS ROBOT CAPABLE OF MULTIMODAL MOTION 849

Fig. 2. Morphological modification in AmphiRobot-II. (a) Reduced fore-and-aft clearance between fish-like modules. (b) Reduced clearance between thethird module and the peduncle (shadow area).

less resistance to fluid flow as well as a more picturesqueprofile [see Fig. 1(b)].

C. Wheel-Propeller-Fin Mechanism

Driving multiple separate propulsive elements via a shaftwithin a tight space is a technical challenge. For the preced-ing AmphiRobot-I, the flipper and wheel that are mounted onthe output shaft of the dc motor (Maxon EC-max 16/GS16A)are interchangeable. The reciprocating flapping flipper acts asa pectoral fin assisting in propulsion and maneuverability inwater, and as a limb for slow crawling on land. The variantwheel with four spokes and four feet does not drive the robotfast enough into the rolling mode as it lacks sufficient motortorque. No doubt, it is very inconvenient to manually switchthe motion modes between the flapping flipper and the rollingwheel, especially inappropriate for autonomous locomotion inever-changing environmental conditions. Moreover, the flipperactuated by the dc motor is not very suitable for fast responseflapping due to low mechanical efficiency caused by frequentstarting–accelerating–braking–reversing in actuators. Addition-ally, to accomplish an overall cycle of online trajectory controlwith an allowance of consuming time for planning and deci-sion, longer time is required, which deteriorates the maximumlocomotion potential of the flippers. Taking all these factors intoconsideration, we propose a novel wheel-propeller-fin mecha-nism where a unique coaxial shaft is utilized to drive the wheelpropeller and the flipper separately. The employment of this hy-brid mechanism permits a distributed control of terrestrial andunderwater locomotion simultaneously that guarantees a betterperformance and more autonomous switch during locomotion.

As illustrated in Fig. 3, the composite coaxial shaft consistsof two independent outputs: the inner shaft and the outer shaft.The former actuated by a servo drives the artificial flipper, whilethe latter actuated by the dc motor drives the wheel propeller.In particular, an extension fixture that has been utilized as asymmetrically assembled coaxial shaft will laterally take up toomuch room in the head unit (only 150 mm in width). An axle-box with a custom-made sealing unit is utilized to combine the

Fig. 3. Integrated wheel-propeller-fin mechanism. (a) Back view. (b) Frontview. (c) Mechanical configuration of a composite coaxial shaft. (d) Manufac-tured parts.

composite shaft with the outside of the side panel by mechanicalmeans. The actuators, i.e., dc motor and servo, are vertically ar-ranged on the inside of the side panel rather than on the bottomof the head adopted in the previous version, which highlightsthe modular concept and simplifies the assembly [see Fig. 3(a)].

As a bonus offered by the new version, a gear set with areduction ratio of 1:2 is utilized by the servo for driving the in-ner shaft, which expands the movable range from 180◦ to 360◦

(noncontinuous) and especially enables the flipper to reverselyflap for backward swimming. Moreover, up-and-down locomo-tion can also be achieved by imposing an angle of attack on thepectoral fin. As for the dc motor (Maxon RE-Max 24 + GP22Cwith a reduction ratio of 53:1) with larger torque, it drives theouter shaft through a bevel gear set corresponding to a revolu-tion direction change of 90◦. The connected wheel propellersacting as drive wheels, in conjunction with a pair of passivewheels attached to the base of the last fish-like propelling unit,achieve fast-moving roll, forward or backward. When spinningunderwater, the specialized four spokes [see Fig. 3(b)] functionas a common screw propeller that can steer the robot by lateralthrust vertical to the fore-and-aft body, i.e., the wheel propellercan be independently used for lateral maneuvers.

As a side effect brought about by the modular design,waterproof-related issues of the wheel-propeller fin should befully considered. To this end, we have devised a specializedsealing unit based on mechanically dynamic seals. The cavumbetween the outer shaft and the axlebox, whose ends are fixedby bearings, is filled with nonhydrophilic, frictionless grease.The inner shaft is positioned and sealed in like manner. Ul-timately, the side panel equipped with the wheel-propeller-finmechanism is mounted into the head via screwing as a module,which facilitates repeated disassembly and assembly. There-fore, the wheel-propeller-fin mechanism can be regarded as amultipurpose propelling tool.


Fig. 4. Newly designed clutch for the swivel mechanism. (a) Mechanicalsketch. (b) Manufactured parts.

D. Swivel Mechanism

Benefiting from the specially designed swivel mechanism, therobot can realize distinctive swimming modes combining fish-and dolphin-like swimming. In the previous version, the servooutput shaft behind the head is inserted into the hole in the frontend of the first modular unit and fixed by a countersunk rivetscrewing vertically from above. Due to the mismachining tol-erance as well as the existing fit clearance, a nonsmooth switchduring swimming, especially an imprecise position transition(not 90◦ in the strict sense), will induce the inclination of therobot’s body. This inclination badly affects the locomotion per-formance. Hence, a newly designed clutch structure shown inFig. 4 has been exploited to overcome the potential contrarious-ness. The clutch is welded to the output shaft and two additionalsmall axes distributed on contralateral sides can assist the out-put shaft in positioning. The prominent improvement lies in theline connection in place of the point connection. This permitsstronger fixing, which facilitates a more smooth switch betweenfish- and dolphin-like modes.

E. Mechanical Implementation

Based on the aforementioned mechanism design scheme, anupdated amphibious robot has been developed. As depicted inFig. 1(b), the robotic prototype with unique wheel-propeller finsmainly comprises a head unit, three fish-like propelling units,and a composite peduncle mechanism followed by a crescent tailfin. To imitate fin elasticity exhibited in fish, a soft elastoplasticmaterial, Roylar, is used for fabricating the tail fin. Meanwhile,more rigid Nylon 66 is exploited for the pectoral fins. The corre-sponding technical parameters of the AmphiRobot-II are listedin Table I.

III. TERRESTRIAL LOCOMOTION CONTROL

A. Body-Deformation-Based Steering Characteristics

As a primary motion pattern, terrestrial locomotion con-trol involves good stability and maneuverability as well asrobust obstacle avoidance [15]–[17]. According to the mechan-ical structure of the AmphiRobot equipped with wheel pad-dles (AmphiRobot-I) or wheel-propeller fins (AmphiRobot-II),wheeled locomotion is the basic mode on land. Taking the bodystructure of the AmphiRobot into careful consideration, the drive

TABLE ITECHNICAL SPECIFICATION OF THE DEVELOPED AMPHIROBOT-II

of the AmphiRobot is more similar to that of a car drive. Theperpendiculars of two mutually independent wheels and thefixed wheels of a car form an instantaneous center of rotation(ICR) that induces the orientation adjustment of the car. Whenthe robot body remains straight, the fore driving wheel-like partand rear passive wheels are parallel, forming no ICR, and therobot moves forward. Benefiting from the carangiform swim-ming in water, the robot’s body shape can be varied when themodular propelling units depart from their central positions.Then the perpendiculars of wheel paddles and passive wheelsintersect where an ICR is formed and the robot can maneuveron land. Such a maneuvering procedure is, hereinafter, referredto as “body-deformation steering.”

For our robot with three fish-like propelling units, the inde-pendent rotation of the second or third unit or their coordinateddeflections will yield a deformed body shape that will form anICR. Therefore, three types of deformation can be deployed tosteer the robot agilely on land. These three methods form dif-ferent ICRs corresponding to different turning radii, which willbe discussed later.

B. Geometry-Based Deformation for Steering

As shown in Fig. 5(a), both the second unit and the thirdone depart from their middle positions with offsets of α and β,respectively. The body shape turns from a straight line into anapproximate arc corresponding to an ICR. Once, the deflectionangles are given, D1 and D2 can be calculated based on thegeometrical relationship of the triangle �PQX

D1

sinβ=

D

sin (π − α − β)D2

sin α=

D

sin (π − α − β)(1)

where D is a constant. As the two right triangles share the samehypotenuse, one can obtain

{sin(α + β − γ) = L1

L

sin γ = L2L

⇒ L1

sin(α + β − γ)=

L2

sin γ(2)

where L1 = D1 + D3 , L2 = D2 + D4 , while D3 and D4 aredetermined by the prototype. Combining (1) and (2), γ can besolved. Then the corresponding turning radius can be expressed


Fig. 5. Illustration of changing the body shape via deflections of the propellingunits to form an ICR. (a) Coordinated deflections of the second and third pro-pelling units. (b) Separate rotation of the second unit. (c) Separate rotation ofthe third unit.

by R = L1 cot(α + β − γ)

R =D (sin α + sinβ cos (α + β)) + D4 sin (α + β)

sin2 (α + β)

+D3 sin (α + β) cos (α + β)

sin2 (α + β). (3)

As a special case shown in Fig. 5(b) and (c), the independentrotation of the second or third unit will also form an ICR. In likewise, the following relations result:

R′ =D + D3 cos α′ + D4

sin α′ (4)

R′′ =(D + D3) cos β′ + D4

sinβ′ . (5)

In order to obtain the optimal turning mode, the radii of threeturning approaches with the same deflection angles will be an-alytically compared. Assume that

α + β = α′ = β′ (6)

where the superscripts correspond to the two particular cases. Itgeometrically follows that the inequality holds as R′′ < R < R′.Fig. 6 plots the comparative result. As can be seen, with the samedeflection, the case employing the third propelling unit to rotatearound its spin axis will generate the minimal turning radius.Additionally, the individual rotation of the third unit causes lessdeviation of passive wheels from the longitudinal centerline,which enhances the robot’s stability.

C. Extension of the Body-Deformation Steering

In light of the modular structure of the AmphiRobot, wecan expand the conclusion to a modular amphibious robot withmultiple joints as a supplement. Assume that the robot has N

Fig. 6. Comparative result for three methods to form ICR.

Fig. 7. Body deformation of a modular robot with N similar modular units.

modular units as shown in Fig. 7, and the deflection angles aredenoted by θ1 , θ2 , . . . , θN −1 , where θi corresponds to the jointangle of the (i + 1)th modular unit relative to the ith one. Thedeformation of N modular units can be viewed as an N -polygonwith N sequentially connected links, and the first modular unitis still attached to the head that constitutes the first link inunion. The lengths of links are denoted by L1 , L2 , . . . , LN ,with (xi−1 , yi−1) and (xi, yi) as the start and end points ofthe ith link. Here L1 denotes the length between (x0 , y0) andthe output shaft of the first unit (corresponds to (x1 , y1)). Thecoordinate system is established in Fig. 7, where (x0 , y0) cor-responds to the origin (0, 0). As the midpoint of the two rearpassive wheels corresponds to the end point (xN , yN ), the ICRis the intersection point of the X-axis and the perpendicular lineorthogonal to the ith link while passing (xN , yN ). The turningradius is then the distance between the ICR and the origin of thecoordinate.

From Fig. 7, the end point (xN , yN ) can be expressed asfollows:

{xN =

∑Ni=2 Li sin(

∑i−1j=1 θj )

yN = L1 +∑N

i=2 Li cos(∑i−1

j=1 θj ).(7)


Let the sum of deflection angles∑N −1

i=1 θiΔ= α, i.e., the included

angle between the Y -axis and the reverse extension line of theN th link. Then we can obtain the line passing (xN , yN ) andperpendicular to the N th link as follows:

y = (x − xN ) tan(π − α) + yN = yN − (x − xN ) tan α.

Let y = 0, and we can get the intersection point

x =yN

tan α+ xN (8)

that corresponds to the turning radius. By substituting (7) into(8), we can obtain the turning radius as follows:

R =L1 +

∑Ni=2 Li cos(

∑i−1j=1 θj )

tan α+

N∑i=2

Li sin( i−1∑

j=1

θj

)

(9)where L1 , L2 , . . . , LN represent the mechanical dimensionsof the robot and only θ1 , θ2 , . . . , θN are undecided variables.Different turning radii will be obtained by applying differentdeflection angles of modular units. Moreover, the overall de-flection angle α will fundamentally determine the turning ra-dius that will be fixed next. Obviously, different parameter sets{θ1 ,θ2 , . . . , θN −1} will generate different turning trajectoriesand radii, which further need to be optimized.

A more general form of (9) can be rewritten as follows:

R(θ1 , θ2 , . . . , θN −1) =L1 +

∑Ni=2 Li cos(

∑i−1j=1 θj )

tan α

+N∑

i=2

Li sin( i−1∑

j=1

θj

)

=L1

tan α+

LN

sinα+

N −1∑i=2

Li

×

⎧⎨⎩

1tan α

cos( i−1∑

j=1

θj

)+ sin

( i−1∑j=1

θj

)⎫⎬⎭

=L1

tan α+

LN

sinα

+N −1∑i=2

Li

sin αcos

(α −

i−1∑j=1

θj

). (10)

It is apparent that the minimum turning radius can be obtained bysetting θi = 0 (i = 1, 2, . . . , N − 2), θN −1 = α, i.e., the min-imum turning radius corresponds to the deflection of the lastmodular unit separately. So the minimum turning radius can bederived as follows:

R =L1

tan α+

LN

sin α+

N −1∑i=2

Li

sin αcos α =

N −1∑i=1

Li

tan α+

LN

sinα

(11)that conforms to R′′ in (5) by substituting D,D3 ,D4 , and β′

for L2 , L1 , L3 , and α individually (N = 3). As demonstrated in(11), the body-deformation steering approach can be expandedto a similar locomotor configuration like our AmphiRobot with

Fig. 8. Configuration of the formulated CPG model. (a) Simplified structure.(b) CPG network configuration.

arbitrary modular units. More importantly, it will offer signifi-cant benefits to the design and locomotion control of modularamphibious robots in the future.

IV. UNDERWATER LOCOMOTION CONTROL

As for underwater locomotion, fish- or dolphin-like swim-ming is the primary locomotion means for the AmphiRobot-II. A large number of methods have been proposed to tacklethis issue [18]. At large, control methods employed can be cat-egorized into two fundamentally different classes: trajectorytracking control and online gait generation control. In the for-mer, predefined swimming modes are usually generated via of-fline planning and online tracking control. A good example isa method to replicate swimming kinematics through fish bodywave fitting [19]. In the latter, swimming gaits are not predefinedin advance, but calculated online. Inspired by lampreys, whosefast axial undulations being propagated as traveling waves aregoverned by activities in its spinal neural network named CPGs,more recent studies use CPGs to generate the desired gaits onlinefor modular designs [20]. In essence, the CPGs are networks ofneurons that can produce coordinated oscillatory signals withoutoscillatory inputs from sensory feedback or from higher controlcenters [21]. More specifically, compared with the sine-basedapproach commonly used in fish-like swimming control, CPG-based control has the advantage of online gait generation andsmooth trajectory transition even with relatively simple con-trol signals [22], [23]. In this paper, an improved CPG modelis responsible for generating the waves of joint activation formultimodal fish- or dolphin-like swimming.

As shown in Fig. 8, a conceived CPG model functionallymatching the mechanical system of the robot is created. It com-prises a pair of pectoral CPGs and a series of tail CPGs. Forthe sake of simplicity and modularity, the pectoral CPG and thetail CPG possess the same structures, which are activated bythe brain and regulated by feedback information. As the cell ofthe CPG model, a phase oscillator with controlled amplitude


in terms of the Kuramoto model is utilized to achieve the syn-chronization of multiple oscillators so as to ensure coordinatedmovements of multiple joints [22], [24]

⎧⎨⎩

φi = 2πfi +∑

j∈T (i) ajwij sin(φj − φi − γij )ai = τi

{τi

4 (Ai − ai) − ai

}χi = ai {1 + cos(φi)}.

(12)

For detailed description of the oscillator model, we refer thereaders to [25]. We just remark here that χi for oscillator irepresents the resultant burst serving as the output signal.

As observed in Fig. 8(b), the tail CPGs include eight oscilla-tors, i.e., O1–O8. Every two oscillators constitute a CPG unitfor each oscillating joint (J1–J4), corresponding to a set of mu-tually inhibited extensor and flexor. The subtraction of output ofthe left and right oscillators in each oscillating joint is utilized toactuate the corresponding servomotor, that is, ϕi = χi+4 − χi

(i = 1, . . . , 4). For the pectoral CPG O9 or O10, its output sig-nal directly serves as the control command to drive the pectoralfin. The actuated joint angle signals of the pectoral fins can becomputed as ϕL = χ9 − a9 , ϕR = χ10 − a10 , which have beenmodulated to be positive–negative.

In order to establish the CPG-based control architecture, abioinspired “saturation function” is introduced to identify theimpact of the input drive on the output of the CPG. Com-pared with the previous research [22], a new saturation functionbuilding a bridge between input drive and oscillator responseis presented. Going back to nature, most of the time, the carp(cyprinoid) devotes part of its tail or caudal fin to propulsionand maintains slow cruising. The whole flexible body is onlyinvolved when speeding up or in high-speed swimming witha higher oscillatory frequency [26]. Loosely inspired from thespeed regulation observed in cyprinoids, an active oscillatorylength-based control strategy is used to achieve that differentlengths of the body participate in the oscillations at variousspeeds. Specifically, two piecewise frequency and amplitudesaturation functions are defined as follows:

fi = gf (d) ={

kf,id + bf,i dlow ,i ≤ d ≤ dhighflow−cut 0 ≤ d < dlow ,i

(13)

Ai = gA (d) ={

kA,id + bA,i dlow ,i ≤ d ≤ dhighAlow−cut 0 ≤ d < dlow ,i

(14)

where d indicates the input drive signal received by the robot,which can further be divided into the left and right drive signalsdL and dR associated with bilateral neural oscillators. flow−cutand Alow−cut represent the low-cut frequency and amplitudewhen oscillations block, respectively. kf,i , bf ,i , kA,i , bA,i standfor frequency coefficients and amplitude coefficients, which de-cide the evolution of the intrinsic frequency and amplitude of theith oscillator. dlow ,i and dhigh are the lower and upper thresholdsseparately. For the ith oscillator, once the drive reaches the cor-responding lower threshold dlow ,i , the homologous oscillationsstart. By regulating the lower threshold dlow ,i , the correspond-ing joint can be enabled or not (e.g., dlow ,i > dhigh ), which canimplement various propulsion modes coordinated by multiplepropulsive elements. These are the same to the pectoral fins,

TABLE IILOCOMOTOR PERFORMANCE COMPARISON

which is denoted by dlow ,pec . Hence, such a flexible controlpolicy will endow the robot with energy-efficient swimming.

Due to the complexity, nonlinearity, and strong coupling un-derlying the CPG models, analytical methods have limited ef-fect on parameter determination. Meanwhile, optimization orlearning-based parameter selection is time consuming and re-quires self-contained sensory devices as a support for onlinesensing and evaluation. In this paper, initial testing of theCPG model is conducted in a dynamic simulation environ-ment for solving swimming performance and parameter explo-rations [27]. Subsequent experiments on the physical robot aredone to refine the preliminary parameter space till a satisfactoryperformance resulted.

Notice that nonrhythmic turning can be induced when asym-metrical drives are applied to the left and right sides of the CPGmodel. The robot will then turn toward the side receiving thehigher drive. Besides the asymmetrical drives inducing turning,the differences in oscillatory frequencies and amplitudes of thepectoral fins on bilateral sides will also assist in turning andstable propulsion.

V. EXPERIMENTS AND DISCUSSION

A. Mechanism Test

In contrast to AmphiRobot-I, as summarized in Table II, theimproved AmphiRobot-II shows an enhanced performance un-der testing. Waterproof tests demonstrate the robot can contin-uously operate about 1.5-h underwater without bearing the riskof water seepage. This will be of great assistance for exten-sive underwater experiments. The updated wheel-propeller-finmechanism facilitates rapid switching of actuators and locomo-tor patterns when adapted to varying environments. As shownin Fig. 9, the robot can adapt to various terrains successfully.

B. Terrestrial Test

To verify the proposed body-deformation steering approach,extensive experiments have been conducted in both field andlaboratory environment. In terms of the aforementioned princi-ple, with the head and the first two propelling units maintaininga straight line during testing, the third unit departs from thecentral position by a specific angle of 37◦ that remains invari-able throughout. The achieved circular motion on the ceramictile-paved floor is depicted in Fig. 10. The measured turningradius is about 550 mm, whereas the calculated radii from (5)is 552 mm. The minor error between the theoretical and experi-mental performances demonstrates the validity of the proposedbody-deformation steering approach.


Fig. 9. Snapshots of moving on different terrains involving: (a) bumpy ground;(b) stone road; (c) soft grassland; and (d) slope.

Fig. 10. Image sequence of performing circular motion via the body-deformation steering. Note that the blue and red lines in two snapshots representthe same locations in the actual ground.

C. Underwater Test

To validate the feasibility of the proposed swimming controlmethods, extensive experiments are carried out in the swimpool and lake. By applying the same drive between the left andright sides of the CPG model, i.e., dL = dR , the AmphiRobotwill perform forward swimming. A general trend is found thatthe forward speed increases directly with the increasing drive.Interestingly, as shown in Fig. 11, the overall profile is evidentlydivided into two distinct phases by point dlow ,1 . In the firststage, besides the increase of frequency and amplitude, the activebody length involved in the swimming rises continually as aresult of the participation of more joints. Nevertheless, all thejoints function and the active body length maintain invariantin the second stage. The two-phase profile demonstrates thatthe oscillating body length predominantly plays an importantrole in the propulsion of the AmphiRobot, and that the createdsaturation function has been effective in this regard. Meanwhile,the influence of the drive difference on the turning radius isexplored. Table III displays four cases of which dL and dR varyin the opposite direction while their means remain constant. Ascan be clearly observed, the drive difference between dL and dR

can greatly impact the turning radius. The bigger the differenceis, the smaller the turning radius will be, which is consistentwith the biological fact [28].

Aside from fish-like propulsion, other locomotive patternssuch as dolphin-like swimming, propeller mode, and land–watertransition are examined. On the one hand, when the swivel mech-anism is rotated 90◦, the CPG model, without any further modi-

Fig. 11. Relationship between drive and forward speed. Note that each exper-imental data point is an average of five repeated trials, and that each data arenot computed from the total distance traveled, but from the distance betweenthe starting and the end points after a certain amount of time.

TABLE IIITURNING RADII WITH DIFFERENT INPUT DRIVES

fication, will successfully take over the dolphin-like swimming.On the other hand, by exploiting the integrated sensory feed-back, autonomous locomotion indicating interaction betweenthe CPG-based control system and the external stimuli becomespossible. For instance, autonomous land–water transition can beelicited by sensory information gathered from onboard liquid-level sensors. We remark that, to rapidly identify the environ-ment, two liquid level sensors are mounted on the bottom ofthe head and the last module adjacent to the peduncle, respec-tively. Only when the last propelling element enters the water,wherein the rear liquid-level sensor detects the liquid state, willthe robot switch from crawling gait to the swimming mode, andvice versa. Fig. 12 shows some on-site experimental scenarioson multimodal motions, which achieve the goal of ensuring ourbuilt propulsive mechanisms a relative satisfactory amphibiousfunction.

D. Discussion

The built amphibious robot, with the aid of the pro-posed design scheme and control methods, exhibits a fairlygood performance on land. However, when performing


Fig. 12. Snapshots of underwater test. (a) Fish-like forward swimming.(b) Turning maneuver. (c) Switch between fish-like and dolphin-like swimming.(d) Propeller mode. (e) Locomotion transition from land to water.

body-deformation-based steering, frequent lateral displacementof the third propelling unit will impose a detrimental effecton the mechanism. To remedy this, the reciprocally rotatingjoint should be well lubricated to eliminate any damping dur-ing long-time operations. For the sake of long-term durability,an integrated design methodology for lightweight materials andsmooth structures should be further investigated.

As for the CPG-centered swimming control, many questionsremain unsolved in the interplay between CPG modeling andonboard implementation. For instance, how to combine rhyth-mic and nonrhythmic motions into a general control framework,how to possibly simplify the artificial CPGs system yet with theadvantages of biological CPGs, and the like, such bottlenecksmight limit extensive applications of the CPG architecture aswell as robotic performance to some extent. More cooperativeeffort should be devoted to developing a more generalized CPGcontrol framework. Notice also that one main drawback of thedeveloped amphibious robot is relatively poor climbing abilityon the slope due to insufficient torque supplied by the dc motorsof the wheel-propeller fins. For this reason, more powerful dcmotors with adequate torque-to-mass ratios will lead to a bettermultimodal locomotion performance both on land and in water.

VI. CONCLUSION AND FUTURE WORK

In this paper, we have presented a novel amphibious robotwith the main emphasis placed on its propulsive mechanismand locomotion control. According to the structure and loco-motion characteristics of the conceived amphibious robot, a se-ries of modifications of the morphological mimicry, the wheel-propeller-fin mechanism as well as the swivel mechanism have

been done. For the terrestrial locomotion, a body-deformationsteering method has been proposed with the minimum turningradius obtained accordingly; moreover, this method is extendedto deal with a modular amphibious robot with N joints. For theunderwater locomotion, a CPG-centered control model is em-ployed, in which bioinspired saturation functions are proposedto accomplish an active oscillatory length-based control strat-egy. Physical experiments further verify the effectiveness of theproposed design. As a bonus, multimodal amphibious motionshave been realized via modulating the CPG parameters or theswitching mechanism.

Future research will concentrate on two aspects: first, greatmechatronic efforts should be devoted to the development ofenhanced amphibious mechanisms; second, parameter tuningand gait optimization by using some optimization techniques(e.g., [29], [30]) will be explored in depth.

ACKNOWLEDGMENT

The authors would like to thank the anonymous reviewersand the Associate Editor for their valuable comments and sug-gestions on improving the manuscript.

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Junzhi Yu received the B.E. degree in safety engi-neering and the M.E. degree in precision instrumentsand mechanology from the North China Institute ofTechnology, Taiyuan, China, in 1998 and 2001, re-spectively, and the Ph.D. degree in control theoryand control engineering from the Institute of Au-tomation, Chinese Academy of Sciences (IACAS),Beijing, China, in 2003.

After graduation, he was a Postdoctoral Re-searcher with the Center for Systems and Control,Peking University, Beijing. From March to August

2008, he was a Research Fellow with the City University of Hong Kong,Kowloon, Hong Kong. From September 2009 to August 2010, he was a GuestResearcher supported by the Alexander von Humboldt Foundation with theDepartment of Informatics, University of Hamburg, Hamburg, Germany. He iscurrently an Associate Professor with the Laboratory of Complex Systems andIntelligence Science, IACAS. He has published over 100 journal and conferencepapers. His research interests include biomimetic robots, multirobot systems,and intelligent information processing.

Dr. Yu serves as an Associate Editor of the Journal of Mechanical Scienceand Technology as well as the International Journal of Information and SystemsSciences.

Rui Ding received the B.E. degree in automationfrom Wuhan University, Wuhan, China, in 2006.He is currently working toward the Ph.D. degree incontrol theory and control engineering at the Insti-tute of Automation, Chinese Academy of Sciences,Beijing, China.

His research interests include mechatronics,biomimetic robotics, and embedded system.

Qinghai Yang received the B.E. degree in measure-ment and control and the M.E. degree in measuringand testing technologies and instruments from Hu-nan University, Changsha, China, in 2002 and 2005,respectively, and the Ph.D. degree in control theoryand control engineering from the Institute of Automa-tion, Chinese Academy of Sciences, Beijing, China,in 2009.

He is currently an Engineer with the Research In-stitute of Petroleum Exploration and Development,Petrochina, Beijing. His research interests include

biomimetics and automation.

Min Tan received the B.Sc. degree from TsingHuaUniversity, Beijing, China, in 1986, and the Ph.D.degree from the Institute of Automation, ChineseAcademy of Sciences (IACAS), Beijing, China, in1990, both in control science and engineering.

He is currently a Professor with the Labora-tory of Complex Systems and Intelligence Science,IACAS. He has published over 100 papers in journals,books, and conferences proceedings. His research in-terests include robotics and intelligent control sys-tems.

Weibing Wang received the B.E. degree from Xin-jiang Institute of Technology, Urumchi, China, in1991. He graduated from the Department of Agricul-tural Mechanization, Zhejiang University, Hangzhou,China, in 2000.

He is currently an Associate Professor withthe Machine and Electricity Engineering College,Shihezi University, Xinjiang, China. His research in-terests include mechanical CAD/CAM and robotictechnologies.

Jianwei Zhang received the Bachelor ofEngineering (with distinction) and Master of Engi-neering degrees from the Department of ComputerScience of Tsinghua University, Beijing, China, in1986 and 1989, respectively, and the Ph.D. degreefrom the Department of Computer Science, Instituteof Real-Time Computer Systems and Robotics, Uni-versity of Karlsruhe, Karlsruhe, Germany, in 1994.

He is currently a Professor and the Head of Tech-nical Aspects of Multimodal Systems, Departmentof Informatics, University of Hamburg, Hamburg,

Germany. His research interests include multimodal information systems, novelsensing devices, cognitive robotics, and human–computer communication. Hehas published over 200 journal and conference papers, technical reports, fourbook chapters, and two research monographs.

Dr. Zhang is a recipient of several awards, including the IEEE ROMANBest Paper Award in 2002 and the IEEE AIM Best Paper Award 2008. He is amember of the organizing committees of numerous international conferences,including some future ones such as IEEE ICRA 2011 Program Cochair, IEEEMFI 2012 General Chair, IROS 2015 General Chair, etc.

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