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Sat, 22 Aug 2009

RCM expansion boards for SRV-1 Blackfin now shipping

The RCM expansion boards with interfaces for 20 servos, 16 A/D, 16 GPIO and microSD are now shipping. The boards can be ordered here:
         Surveyor Online Store.

One of the RCM developers made a short video of the RCM exercising 20 servos simultaneously:


Posted Sat, 22 Aug 2009 13:06 | HTML Link | see additional stories ...



iPhone console for SRV-1 / SVS Blackfin now on Google Code

Thanks to the outstanding work by Nick Kitchener (NickK1066), we now have a working prototype of an iPhone console for the SRV-1 and SVS, hosted on Google Code as GPL Open Source:
        http://code.google.com/p/iphone-srv/



Currently, the console supports live feeds from dual camera SVS (as seen above) or single camera SRV-1, and has the basis of a touchpad joystick interface for motion control, so driving capability is planned but has not yet been added.



A full discussion of the project is found here on the Surveyor Robotics Forum:
        Controlling SRV-1 with iPhone

Posted Sat, 22 Aug 2009 12:45 | HTML Link | see additional stories ...

Mon, 10 Aug 2009

New 4WD motor controller in the works -

As discussed earlier, we have been experimenting with various motor configurations for larger payload versions of an SRV-1 4WD motorized robot base. One of the first prototypes, which hosts an SVS camera head, was briefly described here a few weeks ago -



In the process of testing this configuration, we found that the pan head added significant instability to the camera mounting, and that by reducing the camera mounting to a tilt-only servo with bearing pivots and using on-axis rotation of the robot body, we had the functionality of pan/tilt with greatly reduced camera flop. However, in order to achieve the need position accuracy of the robot rotation, we needed more precise motion control.

The result of this exercise has been the design of a new motor controller, currently designated "srv-4wd-v1". The controller has separate 5A Infineon TLE5205-2G h-bridges for each motor, and should be able to support doubled output by stacking additional h-bridge devices. The motors we have been testing have bearing-supported planetary gearheads and integrated quadrature shaft encoders, and while only rated at 3A stall current, seem to provide adequate power to the 10-lb prototypes. To integrate the encoder data with the PWM motor output, we have added an ARM7TDMI processor (NXP LPC2101) with UART and I2C host interfaces. Using the LPC2101 analog inputs, we have added a battery monitor circuit and headers for 4 Sharp IR ranging sensors. And finally, we have added 2 headers to interface to either 3.3V or 5.0V yaw gyro. Between the encoder and gyro feedback, we should be able to develop a fairly complete dead-reckoning position solution, freeing the host Blackfin processor for higher level navigation tasks.



Board size is 1.5"x2.5" with 1"x2" centered mounting holes. We have started the prototype fabrication and firmware development process, and hope to have first production boards in 4-6 weeks. No idea yet of pricing, but we will post that information once we have working prototypes.

Posted Mon, 10 Aug 2009 11:25 | HTML Link | see additional stories ...

Wed, 05 Aug 2009

Model-free Learning and Control in a Mobile Robot

Sandia National Labs' Biologically Inspired Brain Project (BECCA), first described here, is being presented at ICNC/FSKD 09 conference in Tianjin, China. A copy of the paper is found here - Slearning.pdf

Here is the abstract from the presentation -
      A model-free, biologically-motivated learning and control algorithm called S-learning is described as implemented in an Surveyor SRV-1 mobile robot. S-learning demonstrated learning of robotic and environmental structure sufficient to allow it to achieve its goals (finding high- or low-contrast views in its environment). No modeling information about the task or calibration information about the robot's actuators and sensors were used in S-learning's planning. The ability of S-learning to make movement plans was completely dependent on experience it gained as it explored. Initially it had no experience and was forced to wander randomly. With increasing exposure to the task, S-learning achieved its goals with more nearly optimal paths. The fact that this approach is model-free implies that it may be applied to many other systems, perhaps even to systems of much greater complexity.

Posted Wed, 05 Aug 2009 10:24 | HTML Link | see additional stories ...



SRV-1 RCM Expansion Board now available to order



We are now taking orders for the RCM expansion board (20 servo, 16 A/D, 16 GPIO, microSD), as previously discussed here: Price is $175, with 10% discount for orders placed by education institutions. Order details are found on the Surveyor Online Store.

Note that we only have 50 RCM's available to order. However, if you previously contacted us by email to place an order, don't worry - you are at the beginning of the line and you should hear from us shortly by email.

Posted Wed, 05 Aug 2009 09:54 | HTML Link | see additional stories ...