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[3] G. Caprari, K.O. Arras, and R. Siegwart. The autonomous miniature robot alice: from prototypes to applications. In IEEE/RSJ Inter- national Conference on ...

A Miniature Mobile Robot With a Color Stereo Camera System for Swarm Robotics Research Janne Haverinen, Mikko Parpala and Juha R¨oning Department of Electrical and Information Engineering University of Oulu Oulu, Finland e-mail: {johannes, mparpala, jjr}@ee.oulu.fi

Abstract— In swarm robotics research, instead of using large size robots, it is often desirable to have multiple small size robots for saving valuable work space and making the maintainance of the robots easier. Also, the implementation costs of a miniature robot is lower because of simpler mechanical design. In this paper, we present a novel modular miniature mobile robot designed for swarm robotics research. The sensor set of the robot includes a color stereo camera system with two CMOS cameras and DSP, allowing each robot to do sophisticated stereo image processing on-board. The modular design permits the addition of new modules into the system. The modules communicate using three serial buses (SPI, I2C, and UART), which enable flexible, adaptive, and fast inter-module data exchange. The robot is developed for swarm robotics research with the aim to provide a lowcost and low-power miniature mobile robot with capabilities typically found only in large size robots. Index Terms— mobile robot, swarm robotics, miniaturization, CMOS camera.

I. I NTRODUCTION When a swarm robotics research project, involving a physical multi-agent system, is initiated, one problem is to have a mobile robot platform that has the required capabilities like the right sensor set, a flexible power system, a communication link, and enough computing power, for example. It is often also desirable to implement the multi-agent system by using physically small robots, which permit meaningful research to be done in a limited work space. Today, majority of the commercially available mobile robots are physically large and expensive, which makes them unsuitable for many swarm robotics projects. On the other hand, there is hardly any small size robots available, that have the capabilities required in a state-of-art swarm robotics research. A key feature that has been missing from many miniature robots [3–5], [8], [10] is a color stereo camera system, enabling on-board image processing and analysis, and permitting various surveillance applications. In this paper, we present a novel miniature mobile robot developed in the Computer Engineering Laboratory of University of Oulu, Finland. The robot consists of independent sensor and actuator modules, which reduces

the computation load of the main processor unit. The modular architecture also makes the system extendible. Furthermore, the stereo color camera system permits onboard image processing and image analysis, which is an matched feature in various multi-agent applications. II. D ESIGN

CONSIDERATIONS

The primary goal of this work was to have a modular miniature mobile robot that has functionalities usually found only in large size robots. The robot has to be small permitting the implementation of a large-scale multi-agent system with reasonable implementation costs, and allowing meaningful research to be done in a limited work space. Furthermore, various sensors, including on-board camera, are required in many application oriented research projects. This usually means the usage of large size robots. However, with a right set of sensors, miniature mobile robots can often be used to replace large size robots, in indoors, when manipulation of (heavy) objects is not required. The modularity is also important for enabling the addition of new functions, correcting design flaws, and for permitting the selection of right modules for a given research. For better manufacturability, the mechanics (base) of the robot is made of a single solid plastic part, whose CAD model is shown in Fig. 1. The base holds the DC motors and the lithium-ion battery pack, that can be replaced in a few seconds when recharging is not feasible. The modules are stacked up at the top of the base, while the three bus connectors (visible in Fig. 5) give the necessary mechanical support. The current sensor set was designed for supporting swarm robotics research projects. The stereo camera system was of particular importance for various surveillance applications, which form the primary application area of our research. The stereo camera system can be used for estimating distance, recording stereo image sequences, recognizing objects and colors, producing stereo panoramic views by combining the observations of different robots, and for active sensing, for example. It is also important to have an on-board camera system for giving maximum flexibility and for enabling the implementation of a largescale multi-agent system.

In many applications, in particularly in surveillance applications, the robot needs to know the current date and time in order to be context sensitive. Therefore, a real-time clock is included in the environment module together with a thermometer, a 2-D accelerometer, a visible light detector, and a digital compass. The real-time clock can also be used to power up the robot at regular intervals from a low-power sleep mode. The visible light detector, the digital compass, and the thermometer might be used for particle filter based localization [1], for example. Accelerometer detects vibrations and forces affecting the robot. In surveillance applications, this information can be used to initiate the securing of collected data (robot might be under an attack), for example. The infrared sensor module consists of seven infrared emitters and detectors. It is used as a proximity sensor, and to implement an infrared based communication link. In addition to infrared communication link, the robot has a radio transceiver module enabling inter-robot radio communication and wireless software uploading, which is an important feature in a large-scale multi-robot system. The robot uses a standard 1000mAh mobile phone lithium-ion battery pack as the power source, enabling approximately 4h continuous operation when the stereo camera module is not used, and 2h when the stereo camera module is attached. The power module is responsible of recharging the battery and monitoring its state.

Fig. 1. The CAD model of the base. The diameter of the base is 80mm, and the height is 34mm. The base holds the battery pack, and two DC motors with encoders (325 pulses per revolution) and gear heads (1:22).

III. T HE ARCHITECTURE One configuration of the robot is shown in Fig. 2. In addition to motor and power modules, the robot in Fig. 2 has three other modules, which are (from top): the radio, the environment, and the stereo camera modules, respectively. Each of these modules provide an well defined serial interface for reading or writing data. All modules have an 8-bit low power 8MHz MCU (ATmega32), which

implements the serial interface for accessing the module services, and controls the logic in the module. Each module can have from one to three different serial interfaces (UART,I2C,SPI). While the UART interface is mandatory for each module, I2C and SPI interfaces are optional, and they are used for enhancing the bus performance. Each module with more than one interface can be commanded to switch between interfaces in order to adapt the bus performance. The bus connecting the modules of the robot is presented in Fig. 3.

Fig. 2. The miniature mobile robot developed in the Computer Engineering Laboratory of University of Oulu, Finland. The modules shown here are (from top): the radio, the environment, and the stereo camera modules, respectively. All modules have an 8-bit low power 8MHz MCU (ATmega32), which implements the serial interface for accessing the module services, and controls the logic in the module.

The currently implemented modules are the power, the motor control, the environment monitoring, the radio transceiver, the infrared, the stereo camera, and the ATmega32 based (main) control module, respectively. A 32bit version of the control module is under development, and it will have an on-board Flash memory card for saving data. The power module consists of a recharge circuit, voltage regulators, a charge pump, and a lithium-ion battery monitor. The power module is a special module and it is mounted at the bottom of the base. The motor control module is another special module providing a high level interface to motion system services, which include motion commands, and odometry readings, for example. The motor control module is mounted on the top of the base, and it seals the base. Other modules are independent of the base mechanics. The environment module consists of a real-time clock, a thermometer, a visible light detector, a digital compass, and a 2-D accelerometer. The radio module is based on nRF905 multiband transceiver designed for 433/868/915MHz, and it implements the inter-robot radio communication link. The radio module has 512kB of on-board Flash memory for

temporarily storing uploaded application code. Infrared module consists of seven infrared emitters and detectors, and it is used to detect nearby objects at range 0. . . 300mm. The module implements also an infrared based communication link for a team of robots. The stereo camera module is based on Texas Instrument’s TMS320VC5509 low power DSP and on two TransChip’s TC5740MB24B CMOS camera modules. The camera module has 8MB of SDRAM, and an USB interface for accessing the image data from a standard PC.

8MB SDRAM

16

FIFO 1

8

DSP 144Mhz

8

SPI

8

SPI I2C

CAM 1

FIFO 2

8

CAM 2

64kB EEPROM

BUS

module n

module 2

module 1

3V3 1V8 /reset I2C (400kbit) UART (1Mbit) SPI (2Mbit) INT battery monitor data VCC battery 5V0 GND

Fig. 3. The module bus. The bus has a total of 16 lines including the lines for the power (3.3V, 1.8V, 5.0V, unregulated battery, and ground), the MCU reset, the serial interfaces (I2C, UART, and SPI), the general interrupt (INT), and the battery monitor data, respectively.

IV. T HE STEREO CAMERA

SYSTEM

Fig. 4 shows the block diagram of the stereo camera system shown in Fig. 5. The core of the camera system consists of TMS320VC5509 DSP and two TC5740MB24B CMOS color camera modules. TC5740MB24B has I2C and 8-bit parallel interfaces for accessing the image data, and it can produce 24-bit RGB, YUV or MJPEG image data at VGA resolution at rate 20 frames per second. Two 16kB FIFOs are used for buffering the image data, which allows DSP to do image processing while FIFOs receive new data. MJPEG format enables camera module to store and transmit short stereo video sequences or image pairs (see Fig. 6), which is a useful feature in surveillance applications. However, the radio transceiver, whose maximum transmission rate is 100kBit/s, can send image data off-line only. The DSP software, e.g. an image processing algorithm, is downloaded from the 512kB Flash memory into the DSP at bootup. The software is uploaded into the Flash memory by the MCU, which receives the new code through the module bus. With the help of the radio module, this feature permits the wireless update of the application code, which is an important feature in multi-agent systems. The primary role of the DSP is to do image processing, and extract high level features for the image analysis. MCU communicates with the DSP through the I2C interface and sends the extracted image features through the module bus

MCU 8Mhz

SPI

512kB FLASH

Fig. 4. The block diagram of the stereo camera module. The MCU (ATmega32) connects the module to the bus, receives and saves the new application code for the DSP into the 512kB Flash memory, and uploads the firmware from the 64kB EEPROM into the CMOS cameras through the I2C interface. When MCU resets the DSP, the DSP boots up from the SPI Flash memory. The DSP can use I2C or 8-bit parallel bus with FIFOs for interfacing with the cameras. The 8MB SDRAM is used as a data memory. If required, DSP can bypass the MCU, and interface directly with the other modules, like radio module, through the SPI bus.

to a requesting module. However, the DSP can bypass the MCU by using the SPI bus, and send data directly to the receiving module, thus enhancing the bus performance. This can happen when image data is sent off-line through the radio link, for example. Fig.7 shows example images processed by the camera module. The first image (left) is the original. The second image (middle) is filtered with the 3x3 Sobel convolution mask for detecting vertical gradients. The third image (right) is an edge detected image. Fig. 7 demonstrates how the camera module can be used for extracting salient features from an environment. V. A PPLICATION The miniature mobile, presented in this paper, was developed for a swarm robotics research project initiated in the Computer Engineering Laboratory of University of Oulu, Finland. The project aims to implement a multiagent system composed of state-of-art miniature mobile robots, which are capable of supporting a wide range of applications. The scientific goals of the project are: 1) To understand how a global objective can be achieved by a multi-agent system without explicit regard to cooperation with the other agents. 2) To investigate the relationship of spatial patterns composed of interacting entities (agents), and the resulting dynamics, and to study how this relationship could be utilized [7]. 3) To investigate how humans can effortlessly interact and control a multi-agent system and to have meaningful information about the environment through it. 4) To study what are the minimal requirements for an agent in order to produce useful behaviors at the

VI. C ONCLUSION In this paper, we have presented a novel miniature mobile robot and its on-board stereo color camera system. The robot was design for a swarm robotics research project in which a special attention will be paid on surveillance applications. The application area was one reason for implementing the stereo camera system, as it can be used for detecting moving objects, and for environment monitoring in general. Due to modular design, the base of the robot can be replaced for real world applications where more robust mechanics might be required. The robot also provides an excellent platform for evolutionary robotics research [9] – especially when active vision or perception [2], [6] is evolved and on-board image processing is needed. Fig. 5. The color stereo camera module. The core of the camera system consists of TMS320VC5509 DSP and two TC5740MB24B CMOS color camera modules. The system can produce 24-bit RGB, YUV or MJPEG image data at VGA resolution at rate 20 frames per second.

Fig. 6. A sample stereo image pair. This JPEG image pair was taken with the stereo camera module at VGA resolution (640x480).

Fig. 7. Processing images with the camera module. Left: the original image. Middle: The Sobel filtered image for vertical gradients. Right: The edge detected image.

system level. The robot presented in this paper forms the basic unit of the multi-agent team used in the research.

R EFERENCES [1] S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. A tutorial on particle filters for on-line non-linear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing, 50(2):174–188, February 2002. [2] Ruzena Bajcsy. Active perception. Proceedings of IEEE, 76(8):996– 1005, August 1988. [3] G. Caprari, K.O. Arras, and R. Siegwart. The autonomous miniature robot alice: from prototypes to applications. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’00), pages 793–798, 2000. [4] A. Colot, G. Caprari, and R. Siegwart. Insbot: Design of an autonomous mini mobile robot able to interact with cockroaches. In IEEE International Conference on Robotics and Automation (ICRA’2004), pages 2418–2423, New Orleans, 2004. [5] D. Floreano and F. Mondada. Hardware solutions for evolutionary robotics. In P. Husbands and J-A. Meyer, editors, First European Workshop on Evolutionary Robotics (EVOROBOT’1998, pages 137– 151, Berlin, 1998. Springer-Verlag. [6] I. Harvey, P. Husbands, and D. Cliff. Seeing the light: Artificial evolution, real vision. In From Animals to Animats: Proceedings of the Third International Conference on the Simulation of Adaptive Behavior, pages 392–401, 1994. [7] J. Haverinen and J. R¨oning. Dynamics from patterns: Creating neural controllers with SENMP. In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 2630–2635, Sendai International Center, Sendai, Japan, Sep 28 - Oct 2 2004. [8] F. Mondada, G.C. Pattinaro, A. Guignard, A. Kwee, D. Floreano, J.L Deneubourg, S. Nolfi, L.M. Gambardella, and M. Dorigo. Swarmbot: a new distributed robotic concept. Autonomous Robots, special Issue on Swarm Robotics, 17(2-3):193–221, 2004. [9] Stefano Nolfi and Dario Floreano. Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines. The MIT Press, 2000. [10] G.T. Sibley, M.H Rahimi, and G.S. Sukhatme. Robomote: A tiny mobile robot platform for large-scale ad-hoc sensor networks. In IEEE International Conference on Robotics and Automation (ICRA’2002), Washington DC, Sep. 2002.

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