DESIGN OF A CLIMBING ROBOT: CAPUCHIN

Ruixiang Zhang

Artificial Intelligence LaboratoryComputer Science Department

Stanford University, Stanford, California, 94305, USA

ABSTRACT

This paper describes the work on the design and building ofa climbing robot, Capuchin. The objective of this projectis to create a multi-limbed robot and enable it to free-climbvertical rock autonomously using techniques similar to thoseused by human climbers. To achieve this goal, there are fivefundamental challenges to be considered: hardware design,control, sensing, grasping and planning. Hardware designis particularly critical for a robot. A good hardware designcan increase the performance of the robot and often makeother issues like control and planning easier to deal with. Inthis paper, the hardware design of Capuchin is described indetail followed by a brief introduction of planning and con-trol. Some experimental results are presented at the end ofthe paper.

1. INTRODUCTION

This work is part of an ongoing project at Stanford Univer-sity aimed at designing a robot to free-climb natural verticalrock. ”Free-climbing” implies that only natural features ofthe terrain and friction can be used for climbing. No otheradditional features or gears can be used. Achieving this goalrequires that issues be addressed in five fundamental areas:hardware design, sensing, planning, control and grasping[1]. Previous works have focused primarily on the planning[1, 2, 3] and control problems [5]. This paper presents thehardware design and building of a new climbing robot: Ca-puchin.

Free-climbing robots can be used in construction, search-and-rescue and surveillance tasks, as well as for personalassistance in mountainous terrain or broken urban environ-ments. They can also be applied to planetary exploration onplanets like Mars, where some sites located on cliff faces orin caves have high potential science value.

Various robotic systems have been created to climb ver-tical surface [1-12]. These robots can be classified intothree major categories. Adhesive robots stick to featureless,flat, or smoothly curved surfaces using suction cups [11, 12,13, 19, 20] or magnets mechanism [14, 17]. Consequently,they are limited to environments consisting of glass, metal

Thanks to XYZ agency for funding.

or other smooth surfaces. Robots for engineered environ-ments have end-effectors that match engineered features ofthe environment, like pegs [22], hooks [23], handrails orbars [24, 25, 27], and poles [6, 28]. Robots for inspection ofpipes and ducts rely on frictional contacts with surfaces (asdo free climbers), but take the advantage of geometric reg-ularity to perform precomputed, gaited motion [29, 30, 32].Each of these robots exploits some special property of thesurface for easy grasping or relies on its specific mechanismin order to climb. They could not free-climb uneven verticalterrain.

Lemur is a four-limb free-climbing robot, created by theJet Propulsion Laboratory [33], which is capable of climb-ing artificial rock. Much work has been carried on Lemurrobot and good results have been achieved [1, 2, 3]. How-ever, Lemur also has some limitations. First, it can onlyperform position control on each of its joints. Second, itcannot detect the contact force between a finger and a hold.As a result Lemur might easily fall down a climbing wall bynot applying an adequate contact force. Even small positionerror on the joints could lead to failure.

Figure 1: Capuchin

In order to achieve good free-climbing performance wedesigned and built a new robotic system called Capuchin(Fig. 1). We addressed the main two limitations of Lemur:Capuchin can both control joint torques and sense the con-tact forces at its fingers.

This paper is organized as follows. Section 2 describesthe details of mechanical design and control system config-uration of Capuchin. The planning and control are brieflyintroduced in section 3. Experimental results are providedin Section 4, and finally Section 5 concludes the paper.

2. HARDWARE DESIGN

Hardware design is the first step forward building a robot. Agood hardware design can increase the performance of therobot and often can make other issues like control and plan-ning easier to deal with. Hardware design includes the me-chanical design, control system design and sensors integra-tion. It requires making tradeoffs between a number of fac-tors, e.g.: weight and strength of mechanical parts, weightand torque of actuators, size and performance of sensors andother electronic components. Specially for climbing robot,what kind of force sensors to use and how to mount thembetween a limb and an end-effector are challenging prob-lems.

2.1. Mechanical Architecture

For any type of machine, the design process of the mechan-ical architecture can be examined in several stages, whichare often executed iteratively until a satisfactory solution iffound [34]:

• Step 1: Elaborate a schema of kinematic arrange-ment, determine the topological arrangement of linksand joints, then make a kinematic dimensional instan-tiation.

• Step 2: Choose a type of actuator and transmissionfor each joint, estimate the characteristics of drivingmotors, such as torque, speed and weight, then choosecommercially available components.

• Step 3: Conceive a proper design to position the actu-ators and transmission mechanisms on the ”skeleton”.

Important issues for the mechanical architecture designinclude the number of limbs, the degrees of freedom on eachlimb and the dimensions of each body part. Following thehuman model, we designed Capuchin as a four-limb robot,two limb attached to the upper body and two attached to thelower body. Each limb has three DOFs, one on the elbowjoint (or knee joint for the leg) and two on the shoulder (orhip). The robot has also one rotation joint on the torso be-tween the upper and lower body so that the robot could beable to rotate the upper body and traverse from one face toanother. There should be no special gears on the hand of afree-climbing robot. To simplify the control, a single peg(”finger”) covered with rubber is the end-effector of eachlimb of Capuchin. Fig. 2 shows the ultimate design of Ca-puchin.

There is no standard method to evaluate or optimize amechanical architecture design. While designing the me-chanical architecture of Capuchin, we used simulation to

Figure 2: Simulation of end-effector workspace of 3-D robotcapuchin

evaluate and optimize several parameters. For example, tochoose the ratio of the lower limb length to the upper limblength, we sampled many robot configurations at randomwhen the robot stands on three contacts and checked thekinematic reachability of the fourth limb. The reachablepoints are marked in green color and unreachable points aremarked in red. Then we used statistics method to comparethe reachable workspace for different ratios. The simula-tion results told us that the workspace of the end-effector islarger when the ratio is around 1, i.e., the two parts of thelimb has similar length. We chose 0.93 as the ratio accord-ing to the optimal result of the simulation.

Figure 3: Currently implemented design of Capuchin

Fig. 3 shows the currently implemented design of Ca-puchin. In this design Capuchin has only 2 joints on eachlimb, so that it is a simplified 2D version of the complete

design. This simplification makes control and planning eas-ier. But in the future we plan to extend our implementationto the full design.

Choosing motor and gearhead is critical to the robotdesign. On one hand, we prefer a more powerful motorand higher ratio gearhead to provide more torque. On theother hand, we want to reduce the weight and minimize thegearhead ratio to make the joint back-drivable. Consideringthese factors, we selected Maxon DC motor RE-25-118746and Maxon planetary gearhead GP 32 C 166943 with a ratioof 103 as the actuator set (Fig. 4) for Capuchin.

Figure 4: DC motor with gearhead and encoder

Backlash between motor shaft and body part affects thecontrol performance severely. In order to minimize back-lash, we designed a steel connector with opening and screws(Fig. 5). Steel is used instead of aluminium alloy in order toreduce the deformation of the contacting face. The screwsare used to fasten the connector.

Figure 5: Motor connector

Each limb contains two revolute joints, providing twoin-plane degrees of freedom. Each joint has an identicalactuator, capable of a maximum continuous torque of 10.0N-m. Each end-effector (Fig. 6) is a single peg wrappedin rubber(in fact, the peg is the shaft of a force sensor, asdescribed in 2.2.1).

2.2. Sensors Integration

2.2.1. Force Sensor and End-effector

Selecting a force sensor and mounting it between the limband finger is a challenging problem. On Capuchin, a com-pact strain-gage force sensor is mounted on the end of thelimb and the shaft of the sensor is designed and used as thefinger(Fig. 6). The finger does not have any other featuresto catch the hold except a single peg wrapped with rubber.An amplification circuit is used to drive the sensor and asimple low-pass filter is utilized to filter the high frequencynoise of the output signal.

Figure 6: 3-DOF force sensor and finger

2.2.2. Encoder

As shown in Fig. 4, each motor has a built-in encoder. Theencoders provide us the position, velocity and accelerationinformation of each joint. However, because encoders canonly provide the relative positions rather than absolute po-sitions of the joints, we have to calibrate all the joints everytime before the robot is turned on.

Figure 7: Tilt sensor

2.2.3. Tilt sensor

For control and planning, the robot must be capable of sens-ing the orientation of its body with respect to the gravityvector. A tilt sensor (Fig. 7) is mounted on the body of Ca-puchin. This tilt sensor has two axes and is able to sense thetilt angles in the sagittal and lateral planes.

2.2.4. Video camera

With the help of a video camera (Fig. 8) mounted abovethe finger, the robot can ”see” the holds, allowing visionfeedback during the docking of a finger against a hold.

Figure 8: Video camera above a finger

2.3. Control system configuration

The control system structure of Capuchin is shown in Fig. 9.A computer is used as the command center to send the mo-tion command to the controllers (Fig. 10). The controllersare responsible to receive the command and control the mo-tion of the actuators via a driver board. The controllers alsocollect the sensor data from force sensors, tilt sensor and en-coders and send them back to the computer. The computercommunicates with the controllers through high-speed eth-ernet.

Figure 9: Control system configuration

Figure 10: Controller board

3. PLANNING AND CONTROL

3.1. Planning

A multi-step motion planner is used to plan Capuchin’s tra-jectories. The set of potential contact points are presurveyedand used as the input of the planner. Free-climbing onlyrelies on frictional contact with the surfaces. It requiresstrength, but more importantly it requires deliberate reason-ing: not only must the robot decide how to adjust its pos-ture to reach the next feature without falling, it must planan entire sequence of steps, where each one might havefuture consequences. In the planner, this process of rea-soning is broken into manageable pieces by decomposingthe robot configuration space into manifolds associated witheach state of contact between the robot and its environment.The planner uses a two-stage searching strategy to find afeasible path [3]. First, the planner decides which mani-folds to explore by generating a candidate sequence of footplacements. Then, a one-step planning algorithm based onprobabilistic roadmap (PRM) [35] is use to explore individ-ual manifolds quickly. Probabilistic roadmap approach isused to better handle the interaction between static equilib-rium and the topology of closed kinematic chains.

3.2. Control

There are three basic tasks for the controller of Capuchin:maintenance of equilibrium, joint torque control, finger force,slip and docking control [1]. The position of center of grav-ity (CG) and contact forces on the fingers must be controlledin order to keep equilibrium. The magnitude and directionof contact force will decide the friction on the finger. ACartesian Force Convex (CFC) [5] control is used to controlthe motion of the robot. The desired robot CG trajectory isgiven by the planner. Using PD control, a desired force onrobot CG is generated. Then, the desired force on the robotCG is achieved by allocating the force to all the contactingfingers by a convex optimization technique such as linearprogramming. The controller tracks the planned trajectoryby the feedback information about the robot CG position.Convex optimization achieves the desired force and at thesame time ensures appropriate forces are allocated on each

finger so that the torques do not exceed torque limits and fin-gers will not slip off the holds. Vision feedback can be usedto control the finger docking motion as well as to detect thefinger slippery.

4. EXPERIMENTATION AND RESULT

Fig. 11 shows successive snapshots of a four-step motion ofCapuchin traversing on the vertical climbing wall, on whichholds are randomly distributed. In this experiment, the robotmoves from one set of four holds to another set of four holdsin 20 seconds.

Figure 11: Capuchin traversing a vertical climbing wall

5. CONCLUSION

This paper described the design and building of a climbingrobot, Capuchin. Simulation and statistic algorithms wereused to optimize the kinematic design. There are two im-portant improvement on the hardware design of Capuchincomparing to former climbing robot Lemur: Capuchin canexert force control on each joint and is able to detect thecontact force between finger and hold. These two improve-ments enable Capuchin to climb faster and make it morerobust to disturbances or other uncertainties. Experimentalresults show that Capuchin is capable of achieving multi-step climbing fast and reliably.

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