A Reconfigurable Robotic Exploratory Vehicle for Extreme Environments

**Ayanna Howard, Issa Nesnas, Barry Werger, Dan Helmick**

**Jet Propulsion Laboratory, California Institute of Technology**

**4800 Oak Grove Drive, Pasadena, CA 91109, USA**

Abstract

This paper discusses the development of a new family of reconfigurable
robotic vehicles for use in exploration of the surfaces of Mars and
other remote planets. The robotic vehicle is designed using modular
reconfigurable hardware components and a software architecture that
reconfigures its software capability based on hardware configuration.
This paper will present an overview of the reconfigurable hardware and
software architecture, as well as provide implementation results of
mobile robot traversal on rough terrain.

**1. Introduction**[^1]

Exploration on unknown and uncharted planetary surfaces involves
operating in an unstructured and poorly modeled environment. However,
the lack of precise knowledge about the operating environment makes it
impractical to incorporate every detail necessary to design robotic
systems for multi-task execution. Unexpected changes in the environment,
hardware sensor failures, or changes in task objectives can invalidate
the original design. Most robotic systems are thus designed assuming
complete knowledge of the task specifications and environmental
constraints. This process results in robotic systems that are expensive
to design as well as reduces the robot's ability to robustly deal with
unplanned environmental changes or unexpected system failures.

In order to guarantee success of robotic missions for the future,
technologies that can enable multi-rover colonization and human-robot
interaction must be matured. The main hurdle with this focus is the cost
and system complexity associated with deploying multiple rovers having
the capability to survive long periods of time, as well as possessing
multi-tasking capability. To address this issue, our research focuses on
modularizing both hardware and software components to create a
reconfigurable robotic explorer. This work thus allows the deployment of
rovers on a planet's surface that can ensure robust operation in face of
system reconfiguration, hardware failure, changes in task
specifications, or alterations in environmental constraints.

The construct of our reconfigurable robotic explorer consists of two
sets of components: a set of robotic transporters and a set of science
modules. The robotic transporters, which are all identical, form our
simplest autonomous explorers. These transporters are able to traverse
rough terrain using on-board computational and power resources. Their
symmetrical design with large wheels enables them to operate in any
stable state and recover from drops off small cliffs. Conversely, the
science modules have no mobility. They carry different science
instruments and share only an identical interface. From these two
modules, different mobility platforms can be assembled. Connecting two
robotic transporters to each end of a science module forms a
science-enabled explorer. Additional robotic transporters and science
modules can be added at either end to form a mobile train of science
instruments.

**2. Background**

The approach we utilize to develop our reconfigurable robotic explorer
is to begin with the basic building blocks of a modular 2-wheeled
robotic vehicle called the *Axel*2 \[1\]. An *Axel*2 includes a caster
wheel attached to an axle by an actuated caster link (Figure 1). This
robotic design was developed to address some of the long-term goals for
modular and reconfigurable surface explorers. Compared to four- and
six-wheel rocker-bogie rovers \[2-4\], the design for our reconfigurable
robotic explorer uses a simpler mechanism to carry out similar maneuvers
using less power. Unlike the former rovers, the wheel sizes can vary
without having to scale the reconfigurable design. Also, the loose
coupling in the multi-*axel* systems reduces the stress on the mobility
mechanism, which occurs in rigid vehicles during steering.

Previously, the use of two-wheeled robots has been explored by several
researchers at the University of Minnesota \[5\]. The team has developed
small cylindrical explorers (a few centimeters in diameter) that are
ejected from a cannon mounted on a traditional rover platform. These
explorers are controlled by embedded microprocessors and sensors. In
addition to exploring surrounding areas (mainly flat terrain), these
cylindrical explorers can hop a few centimeters over small barriers. A
commercially available robot from Probotics, Inc \[6\], also uses
two-wheeled locomotion. In contrast with these two-wheeled systems, our
*Axels* have a unique castor link, are an order of magnitude larger, and
are designed for rough terrain exploration. The *Axels* use stereo
vision for obstacle detection and avoidance, and are designed to
interface with science modules to create extendible explorer
configurations.

Several researchers are pursuing a different approach to reconfigurable
surface exploration. Their main concept focuses on highly redundant
robotic systems using very small and modular components \[7-9\]. These
components can be either all identical or selected from a fixed
inventory set. The components can autonomously attach to and detach from
each other, creating a large number of potential configurations. In the
limit as the components get smaller, the robotic system will resemble
moldable "digital clay." In his early work at Stanford University, Yim
\[10\] studied, simulated, and implemented a set of these highly modular
systems, which he termed "polypods". In more recent work at XeroxPARC,
Yim further improved the design of the small modules \[11\]. While
simulations of this work have been very promising, actual
implementations of these systems present serious challenges with today's
actuation and sensing technologies. In other work, Dubowsky and
colleagues at MIT are studying similar systems with a short-term goal of
developing a hybrid system combing traditional rover technologies with
these highly modular and reconfigurable components \[12\]. Unlike Yim's
work, which uses identical components, researchers at MIT are using a
set of fixed components. They introduce the concept of articulated
binary elements (ABE) for actuation to simplify the control of these
systems. Other work that focuses on the development of low-level
reconfigurable robots includes the work of Sanderson at RPI in which a
modular reconfigurable parallel robot was designed \[13\] and Khosla at
CMU, whose team developed the I-Cubes system, a self-reconfigurable
system consisting of a collection of independently controlled
mechatronic links and passive connection cubes \[14\].

Previous research at JPL focuses on utilizing kinematic reconfiguration
for robots operating on rough-terrain \[15\]. Developing a methodology
for kinematic reconfiguration on a real robot continues with the work of
Schenker, et al. \[16\]. Schenker at JPL, in conjunction with
researchers at CMU, MIT, and the U. of Nebraska, is integrating various
technologies in virtual prototyping, control, and sensing, for the
implementation of highly reconfigurable systems. These efforts have
taken a different approach to modular reconfigurable design and focus on
real-time reconfigurable control to alter the robotic vehicle's geometry
in response to changes in the terrain conditions.

**3. The Reconfigurable Exploratory Vehicle**

The approach we utilize to develop our reconfigurable robotic explorer
is to begin with the basic building blocks of a modular 2-wheeled
robotic vehicle called the *Axel*2[^2]. Its symmetric design enables it
to operate in any stable state (e.g. right side up or upside down). This
increases its robustness in traversing unknown terrain and in recovering
from unexpected drops off small cliffs. Each of the two large wheels is
controlled by a separate servo-actuator. A third servo actuator controls
the motion of a link carrying a passive castor wheel. The caster link
provides an additional applied force for increasing traversal capability
over large rocks and in rough terrain. The rotational motion of the
caster link is also used to control vehicle tilt, such that embedded
sensors can be commanded to point in any direction. By coordinating the
motion of the drive wheels and the castor link, the *Axel2* can either
move or rotate its body. When both wheels are driven in the same
direction, the *Axel2* will move forward. To steer the Axel2,
differential control of the wheels is used.

Contained within the axle of the robotic vehicle are different
functional devices - a PC104 processing stack, the three actuators, and
the mechanisms necessary for driving the main wheels and the caster
link. The axle also houses a stereo camera pair of sensors used to
determine navigational direction, extract necessary science, and assist
in docking maneuvers. Rechargeable batteries are placed at the
boundaries of the axle in order to offset the weight felt along the axle
length.

![](media/image1.png){width="3.2708661417322835in"
height="1.791732283464567in"}As an individual module, the *Axel*2
functions as a simple modular robotic vehicle with simple sensing
capability. It can traverse rocks over half its wheel diameter and
perform vision-based operations during autonomous exploration. When
additional capabilities are required, individual modules are linked
together to form a more complex entity. To promote this reconfiguration
process, each *Axel*2 is designed with a module interface that allows
multiple *Axel*2s to be combined with intelligent instrument modules
(Figure 1). This electromechanical module interface is centered on the
midsection of the axle. The *Axel2* carries the female parts of the
mating mechanism while the science module carries the male parts. The
coupling between the *Axel2* and the science module uses a conical
surface that corrects for small misalignment (necessary for autonomous
attaching).

Figure 1. Combining two *Axel*2s with an intelligent instrument module
to increase functionality.

The intelligent instrument module provides additional task functionality
for the reconfigurable robot. It is defined as any enhancing apparatus,
such as a manipulator arm, spectrometer, camera, etc. that allows for
task fulfillment. Unlike *Axel2s*, which are all identical, the science
modules have different designs to support their science instruments. The
science modules are responsible for supplying the actuation/sensing
package necessary for the proper positioning and operation of its
instruments. Each instrument module contains additional computational
power that allows processing of input data, control of mechanical
devices, and enables close interaction with the environment. The module
interface, which contains electrical and mechanical connections, allows
succinct mating of these instrument modules with *Axel*2s and provides
direct communication between modules via a serial connection.

Since many challenges still exist with sensing and perception for
planetary surface robotics \[17\], we will present the design of a
simple science module to demonstrate the concepts of interfacing with
the *Axel*2. This allows us to address the three following areas: (i) a
demonstration of the attaching capabilities of modules, (ii) the
development of the hardware and software architectures for hot swamping
and functional operation, and (iii) the distributed motion control for
the reconfigurable robot vehicle, without dealing with the difficulty
imposed with high-risk approaches to sensing.

### 4. Software control for Axel2

To enable self-diagnosis and automatic reconfiguration of modular
hardware components, *Axel*n is coupled with a software architecture
that provides for autonomous adaptation to hardware reconfiguration. The
reconfigurable software architecture \[18\] consists of simple, general,
reusable code development and enables robust and reliable operation
during task execution. Specifically, the self-reconfigurable software
architecture enables *Axel*n to determine when *physical
reconfiguration* is necessary (e.g., in response to task requirements or
hardware failure), controls such reconfigurations, and performs
*software self-reconfiguration* to conform to the resultant new hardware
configurations.

The reconfigurable modular robotic explorer allows a long-term presence
to exist on remote planets by providing the capability to
repair/replace/reconfigure modules to cope with unexpected events while
maintaining accomplishment of functional goals. Since modules, which may
be *Axel*2s, effectors, or science instruments, are combined as
necessary to meet science goals and mobility requirements, the
corresponding software must be capable of enabling this technology. An
example of a robotic explorer reconfiguration might involve two *Axel*2
modules docking to each side of a science module in order to perform
experiments at a science site, then exchanging the science module with a
manipulator arm in order to perform a coring task. Another
reconfiguration opportunity may occur in response to terrain traversal
difficulties (e.g., adding a \"tether\" module for cliff descent) or for
replacement of a failed mobility or science module that was discovered
during task execution.

The ability to autonomously reconfigure the robotic hardware components
depends heavily on the supporting software. One of the goals of the
*Axel*n system is to increase system simplicity and component generality
through modularity. The reconfigurable software architecture mirrors
this framework by providing a system in which, as *Axel*n
hardware-modules are dynamically docked together or disconnected, their
associated software modules employ the same capability.

The reconfigurable software architecture blends state-of-the-art
techniques of distributed robotic control systems, intelligent
environmental sensing, and self-reconfiguration to support hardware
configuration and task constraints. Task constraints and environmental
sensing are used to determine mobility needs and enable software
pertaining to appropriate hardware modules to drive the initial hardware
configuration process; software will then reconfigure itself for task
performance and in response to task needs, occurrence of unexpected
situations, or detection of hardware failures.

The reconfigurable software architecture involves linking together
reusable software modules through connections with other software
modules or through connections with external resources, such as science
instruments, effectors, or *Axel*n wheel motors. Resource connections
are external to the software modules and allow for communication and
connection with the physical environment. This allows software modules
to receive, as input, data from sensor devices, as well as transmit
commands to hardware components, such as wheel motors. A software module
can have an unlimited number of incoming and outgoing connections. When
data arrives at a module, either from another module or from external
sensors, the data is propagated along that module's outgoing
connections. In order to achieve various forms of functionality, data
flow can be modified through suppressive, inhibitory, or overriding
behavior. Software modules are thus easily reconfigurable and
interactions with connections between modules can be modified
dynamically. The reusable software modules have many different levels of
functionality. At one level, basic software modules are constructed to
enable different forms of rover mobility as dictated by an *Axel*2
versus an *Axel*4 robotic explorer. At another level, software modules
exist that take as input imagery data and determine the number of
modules necessary to construct an *Axel*n to enable descent over a steep
cliff. These reusable software modules are designed to enable various
levels of robotic control such that fundamental functionality can be
achieved.

5\. Implementation

The *Axel2* robot is a two-wheeled robotic vehicle capable of
reconfiguring into a multi-wheeled robotic vehicle of length *n*. Figure
2a shows a close-up of the actual vehicle designed and developed as an
*Axel2*. To test the capability of the robotic exploratory vehicle, we
demonstrate hardware reconfiguration of an *Axel2* robot to an *Axel4*
robot using vision-based docking, and validate the software
reconfiguration process through dynamic modification of the explorer's
mobility pattern based on changes in the hardware configuration.
Vision-based docking involves the process of *Axel*2 identifying the
interface module located on the science module, approaching the docking
connector, and mating. Figure 2b displays a close-up of the docking
connector while Figure 3 give a graphical depiction of the process. A
simple science module is shown to demonstrate the concepts of
interfacing with the *Axel*2. In this series of tests, we were able to
demonstrate the attaching capabilities of the modules, hot swamping and
functional operation of the hardware and software architectures, and
navigation control of the reconfigurable robot vehicle.

![](media/image2.jpeg){width="2.0in" height="1.3125in"}

Figure 2. (a) *Axel2* reconfigurable robotic explorer (b) *Axel2*
docking maneuver

The reconfigurable software architecture was first tested in adapting
the navigation capability of the Axel2. This consists of autonomously
determining the best mode of navigation operation depending on the
hardware configuration (Axel2 vs. Axel4). This allows the same software
architecture to reside on individual Axel2 systems, and yet control the
mobility of the Axel4. For implementation purposes, the software was
tasked to recognize current robot configuration and differences in
hardware, and run different navigation schemes autonomously. The
navigation scheme for an Axel2 consisted of driving the wheels either
forward, or backward. Once mating occurred, such that an *Axel*4 is
constructed, the software reconfigures the robot vehicle's mobility
pattern by autonomously selecting a "front" for instantiating the
steering and navigation control process.

Figure 3. Process of reconfiguring *Axel*2 to *Axel*4

In our tests, we were able to successfully show autonomous
reconfiguration of the software and hardware structure. Tests were also
run to show the capability of the Axel2 to successfully climb over rocks
of half a wheel diameter in height.

### 

### 6. Conclusion

The ability of the *Axel* explorers to change their mobility systems to
adapt to the terrain difficulty is an important capability in surface
exploration. The robotic explorer design allows for robust multi-task
implementation for operation in natural terrain. The advantage of our
approach focuses on the development of both modular hardware and
software components to enable reliable functionality. These vehicles can
be integrated in a wide variety of robotic applications -- from
exploration of remote unknown environments to autonomous scouting for
victims of natural hazards on Earth. Future work will focus on enhancing
the science module capability and performing extensive tests of task
operations in hazardous terrain.

### 7. References

1.  I. Nesnas, "Reconfigurable Exploratory Robotic Vehicles," NASA Tech
    Briefs, Jul 2001.

2.  D. Bickler, "A family of planetary vehicles," Proc. of the Intern.
    Symp. on Mission Technologies and Design of Planetary Mobile
    Vehicles, France, 1992.

3.  P. S. Schenker, et al., "New Planetary Rovers for Long-range Mars
    Science and Sample Return," Proc. Intelligent Robots and Computer
    Vision XVI, pp. 2--15, Boston, MA, 1998.

4.  R. Volpe, J. Balaram, T. Ohm, and R. Ivlev, "Rocky 7: a net
    generation rover prototype," Journal of Advanced Robotics, 11(4)
    December, 1997.

5.  Paul E. Rybski, et al., \"A Team of Robotic Agents for
    Surveillance\", Agents 2000*,* Spain, June 2000.

6.  Probotics, Inc., "Cye-RS" personal robot,
    http://www.personalrobots.com.

7.  I.M. Chen and J.W. Burdick, "Enumerating the non-isomorphic assembly
    configurations of a modular robotic system," Int. J. of Robotics
    Research, vol. 17, no. 7, pp. 702-719, 1998.

8.  G. Chirikjian, A. Pamecha, I. Ebert-Uphoff, "Evaluating Efficiency
    of Self-Reconfiguration in a Class of Modular Robots," Journal of
    Robotic Systems, pp317-338, Vol.13, No.5, 1996.

9.  C. Leger. "Automated Synthesis and Optimization of Robot
    Configurations: An Evolutionary Approach," Ph. D. Thesis, Carnegie
    Mellon University, December 1999.

10. M. Yim, "Locomotion with a unit modular reconfigurable robot," Ph.D.
    dissertation, Dept. of Mechanical Engineering, Stanford University,
    1994.

11. M. Yim, D.G. Duff, K.D. Roufas, L. Kissner, "Polybot: Demonstrations
    of a modular reconfigurable robot," Video Proc. IEEE Int'l Conf. on
    Robotics and Automation, 2000.

12. S. Farritor, S. Dubowsky, N. Rutman, J. Cole, "A system level
    modular design approach to field robotics," IEEE Intern. Conf. on
    Robotics/Automation, Minneapolis, pp. 2890-5, 1996.

13. A. C. Sanderson, [TETROBOT: A Modular Approach to Reconfigurable
    Parallel Robotics]{.underline}, Kluwer Academic Press, 1997;

14. C. Unsal, H. Kiliccote, P. K. Khosla, "I(CES)-Cubes: A modular
    self-reconfigurable bipartite robotic system," Proc. Sensor Fusion
    and Decentralized Control in Robotic Systems II, Boston, MA, pp.
    2-8, Sep. 19-22, 1999.

15. S. Sreenivasan, B. Wilcox, "Stability and traction control of an
    actively actuated micro-rover," Journal of Robotic Systems, 11(6),
    pp. 487-502, 1994

16. P. S. Schenker, et al., "Reconfigurable robots for all terrain
    exploration," Proc. Sensor Fusion and Decentralized Control in
    Robotic Systems III, 15 pp., Boston, MA, 2000

17. E. Tunstel, A. Howard, "Sensing and Perception Challenges in
    Planetary Surface Robotics," IEEE Sensors, Orlando, FL., June 2002.

18. B. Werger, \"Ayllu: Distributed Port-Arbitrated Behavior-Based
    Control,\" Distributed Autonomous Robotic Systems 4, Lynne E.
    Parker, George Bekey, and Jacob Barhen (eds.), Springer, 2000:25-34.

[^1]: ^^ This research was carried out at the Jet Propulsion
    Laboratory, California Institute of Technology, under a contract
    with the National Aeronautics and Space Administration.

[^2]: To provide clarification, the *Axel*n denotes a reconfigurable
    robot having *n* main wheels