Page 63 - ASME DSCC 2015 Program

Technical Program

Adaptive RGB-D Visual odometry for Mobile Robots: An Experimental InVITED SESSIon
Study 2-3-1 TP6 Collision Advoidance and Rollover Prevention (AVS)
Contributed regular paper. DSCC2015-9829 Emerson Burkhart B 4:00pm–6:00pm
J. Wesley Anderson, Joshua fabian, Garrett Clayton, Villanova University,
Villanova, PA, United States Session Organizer: Mahdi Shahbakhti, Michigan Technological University
Session Organizer: Giorgio Rizzoni, Ohio State University
In this paper, experiments are presented in support of an adaptive col-
Session Chair: Craig E. Beal, Bucknell University
or-depth (RGB-D) camera-based visual odometry algorithm. The goal of
Session Co-Chair: Beshah Ayalew, Clemson University
visual odometry is to estimate the egomotion of a robot using images from a
camera attached to the robot. This type of measurement can be extremely
A Discrete-Time Integral Sliding Model Predictive Control for obstacle
useful when position sensor information, such as GPS, in unavailable and
Avoidance of Ground Vehicles
when error from other motion sensors (e.g., wheel encoders) is inaccurate
Invited session paper. DSCC2015-9741
(e.g., due to wheel slip). In the presented method, visual odometry algo-
Yi-Wen liao, J. Karl Hedrick, University of California, Berkeley, Berkeley,
rithm parameters are adapted to ensure that odometry measurements are
CA, United States
accurate while also considering computational cost. In this paper, live experi-
ments are performed that show the feasibility of implementing the proposed In this paper, a robust control architecture is proposed for lane-keeping and
algorithm on small wheeled mobile robots. obstacle avoidance of autonomous ground vehicles. A two-level hierarchical
controller is used to separate the planning and tracking problems. At the
Dynamic Modeling of Robotic fish Caudal fin With Electrorheological
higher-level, we solve a nonlinear model predictive control (MPC) problem
fluid-enabled Tunable Stiffness
with an oversimplified point-mass model. The desired trajectories are gen-
Contributed regular paper. DSCC2015-9879
erated and fed into the lower-level controller, where a force-input nonlinear
Sanaz Bazaz Behbahani, Michigan State University, Okemos, MI, United bicycle model is considered to set up the tracking control law. Moreover, at
States, xiaobo Tan, Michigan State University, East Lansing, MI, United each time step, a linearized bicycle model is derived and implemented to
States
reduce the real-time computational complexity. Based on the above profile,
In this study, we investigate the modeling framework for a robotic fish a discrete-time integral sliding MPC (DISMPC) technique is used to improve
actuated by a flexible caudal fin, which is filled with electrorheological (ER) the system robustness. By introducing an additional sliding control term
fluid and thus enables tenable stiffness. This feature can be used in into the feedback control law, the system trajectories can be maintained
optimizing the robotic fish speed or maneuverability in different operating within a quasi-sliding band. In this case, it becomes necessary to take into
regimes. The robotic fish is assumed to be anchored and the flexible tail account the system dynamics induced by the sliding control. Namely, the
undergoes undulation activated by a servomotor at the base. Lighthill’s state and the input constraints of the MPC problem at each level need to be
large-amplitude elongated-body theory is used to calculate the tightened. This helps to guarantee the feasibility of the original constrained
hydrodynamic force on the caudal fin, and Hamilton’s principle is used to problem in the presence of disturbances. Simulations have been carried out
derive the dynamic equations of motion of the caudal fin. to verify the effectiveness of the proposed controller. The results show that
The dynamic equations are then discritized using the finite element method, the controller is able to simultaneously achieve lane-keeping and obstacle
to obtain an approximate numerical solution. In particular, simulation is avoidance with uncertain friction coefficients.
conducted to understand the influence of the applied electric field on the
An MPC Algorithm With Combined Speed and Steering Control for
stiffness and thrust performance of the caudal fin.
obstacle Avoidance in Autonomous Ground Vehicles
Invited session paper. DSCC2015-9747
jiechao Liu, jeffrey Stein, Tulga ersal, University of Michigan, Ann Arbor,
MI, United States, Paramsothy Jayakumar, U.S. Army RDECOM-TARDEC,
Bloomfield, MI, United States
This article presents a model predictive control based obstacle avoidance
algorithm for autonomous ground vehicles in unstructured environments.
The novelty of the algorithm is the simultaneous optimization of speed and
steering without a priori knowledge about the obstacles. Obstacles are de-
tected using a planar light detection and ranging sensor and a multi-phase
optimal control problem is formulated to optimize the speed and steering
commands within the detection range. Acceleration capability of the vehicle
as a function of speed, and stability and handling concerns such as tire
lift-off are taken into account as constraints in the optimization problem,
whereas the cost function is formulated to navigate the vehicle as quickly as
possible with smooth control commands. Thus, a safe and quick navigation
is enabled without the need for a preloaded map of the environment. Simu-
lation results show that the proposed algorithm is capable of navigating the
vehicle through obstacle fields that cannot be cleared with steering control 63
alone.