Engineers find it of importance to have a quantitative understanding of the charge-depletion characteristics of the battery-bank that powers a mobile unmanned ground vehicle (UGV) so as to have mission-duration, cost-of-transport, range, and other useful estimates. Data analysis to determine the energy use of a ‘large’ wheeled robot – the Clearpath™ Warthog – with Gross Vehicle Weight (GVW) 590 Kg. -- are here discussed. The analysis is based on gravel-surface, straight-path level trials. The results of this analysis inform how far the UGV can travel over the specified surface. We give basic methods for obtaining expected energy usage: tables with estimates for cost of transport and for mission range. Included in the analysis is a nonparametric method for identifying and dealing with the small number of ‘outlier,’ readings that often occur in field trials.
This paper presents results from an experiment performed at the Combat Capabilities Development Command, Army Research Laboratory, Autonomous Systems Division (ASD) on the precision of a 7-degree-of-freedom robotic manipulator used on the RoMan robotic platform. We quantified the imprecision in the arm end-effector final position after arm movements ranging over distances from 362 mm to 1300 mm. In theory, for open-loop grasping, one should be able to compute the final X-Y-Z position of the gripper using forward kinematics. In practice, uncertainty in the arm calibration induces uncertainty in the forward kinematics so that it is desirable to measure this imprecision after different arm calibrations. Forty-one runs were performed under different calibration regimes. Ground truth was provided by measuring arm motions with a Vicon motion capture system while the chassis of the platform remained stationary during the experiment. Using a digital protractor to align the arm joints to the ground plane for a “Level” type calibration, the average total offset of the gripper in 3D space was 19.6 mm with a maximum of about 30 mm. After a “Field” (i.e. Hand-Eye) calibration, which aligned fiducials on the joints, the average total offset came to 37.8 mm with a maximum of about 80 mm. Distance travelled by the arm was found to be uncorrelated with total offset. The experiment demonstrated that Total (X, Y, Z) Offset in the gripper final position is reduced significantly if the robot arm is first calibrated using a standard “Level” calibration. The “Field” calibration method results in a significant increase in Offset variation.
As robots are deployed in more dynamic and uncertain environments, the ability to recover from tip-over events is critical. Previously, a framework for generating quasi-static self-righting solutions for generic robots was developed. This paper extends that framework to include the use of inertial appendage methods. It begins by reviewing the basic framework and discussing how it may be extended to incorporate dynamic solutions. It then discusses the generation of appendage momentum in the presence of ground reaction forces by utilizing the zero moment point concept. This concept is further extended to controlling the momentum transfer between the appendage and the body such that a desired tip-over event results. After initiating the tip-over event, the motion of the appendage may further be controlled to reduce the energy of the impact to land within the basin of attraction, or to increase the energy to intentionally land outside that basin and continue the roll. Four strategies based on this methodology are introduced, permuting appendage acceleration or deceleration and whether or not the appendage is involved in the resulting ground contact. The strategies are compared based on three optimization metrics: energy required to induce tipping, collision energy, and stability margin. Finally, the proposed methods are validated on a physical robot, demonstrating the improvement to its rightability as compared with quasi-static solutions.
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