This paper presents a design approach for rigid wheels operating in highly variable, deformable terrain to improve the mobility, reliability, and efficiency of an autonomous vehicle driving on snow. The longstanding Bekker-Wong theory of terramechanics is used as the basis for the design changes with the wide range of terrain parameters for snow serving as inputs to the models and bounds for the problem. Modifications to the wheel width and diameter are evaluated based on their impacts to the rover as a system, with their effects on torque and drawbar pull being weighed against the resultant modifications in component sizing, rover weight, and energy use. Other factors, not included in the Bekker-Wong models but studied in single-wheel testbed experiments, such as bulldozing resistance and the observed dynamic effects of slip-sinkage, were also considered in the design decisions for the new wheel. Finally, to test these theories and assess the mobility improvements of the new design in situ, a four-wheeled rover, FrostyBoy, was developed for the new wheels and trialed in unmodified snow. While qualitatively showing an improvement in mobility on the Greenland ice sheet, the tests also uncovered dynamic modes of immobilization, in low cohesion, low stiffness snow that are not accounted for in terramechanics theory and require further investigation for trafficability to be maintained in all snow conditions.
more »
« less
PROPRIOCEPTIVE SENSING OF TERRAIN FORCES BY COMPLIANT, FOUR-WHEELED ROVING MODULES
This paper presents a class of four-wheel drive autonomous robots designed to collaboratively traverse terrains with a deformable upper layer, where soil properties result in limited traction and have the potential to cause immobilization. The robots are designed to have front and rear axle yaw degrees of freedom, and front and rear axle roll degrees of freedom providing ground compliance and maneuverability on friable terrain. These degrees of freedom, along with four individually driven wheels and an actuated translational degree of freedom inside a mid-frame joint, enable poses and modes of mobility that differ significantly from a rigid vehicle. A primary goal of this work is to assess the capacity to use this vehicular form as a testbed that leverages these vehicle dynamics to assess mobility. Using a custom ROS-Gazebo simulation environment, a heterogenous driving surface is created and used to evaluate this capability. We show that the vehicle can sense imbalanced terrain resistances proprioceptively. Additionally, we show that rigidity of the vehicle can be controlled through a simple feedback control loop governing the robot’s unconstrained axles to maintain a proper heading angle and still can provide an avenue to monitor the dynamics related to full-vehicle immobilization.
more »
« less
- Award ID(s):
- 1824687
- NSF-PAR ID:
- 10304352
- Date Published:
- Journal Name:
- Proceedings of the ISTVS 20th International and 9th Americas Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Industrial robots, as mature and high-efficient equipment, have been applied to various fields, such as vehicle manufacturing, product packaging, painting, welding, and medical surgery. Most industrial robots are only operating in their own workspace, in other words, they are floor-mounted at the fixed locations. Just some industrial robots are wall-mounted on one linear rail based on the applications. Sometimes, industrial robots are ceiling-mounted on an X-Y gantry to perform upside-down manipulation tasks. The main objective of this paper is to describe the NeXus, a custom robotic system that has been designed for precision microsystem integration tasks with such a gantry. The system tasks include assembly, bonding, and 3D printing of sensor arrays, solar cells, and microrobotic prototypes. The NeXus consists of a custom designed frame, providing structural rigidity, a large overhead X-Y gantry carrying a 6 degrees of freedom industrial robot, and several other precision positioners and processes. We focus here on the design and precision evaluation of the overhead ceiling-mounted industrial robot of NeXus and its supporting frame. We first simulated the behavior of the frame using Finite Element Analysis (FEA), then experimentally evaluated the pose repeatability of the robot end-effector using three different types of sensors. Results verify that the performance objectives of the design are achieved.more » « less
-
We present a bottom-up coarse-graining (CG) method to establish implicit-solvent CG modeling for polymers in solution, which conserves the dynamic properties of the reference microscopic system. In particular, tens to hundreds of bonded polymer atoms (or Lennard-Jones beads) are coarse-grained as one CG particle, and the solvent degrees of freedom are eliminated. The dynamics of the CG system is governed by the generalized Langevin equation (GLE) derived via the Mori-Zwanzig formalism, by which the CG variables can be directly and rigorously linked to the microscopic dynamics generated by molecular dynamics (MD) simulations. The solvent-mediated dynamics of polymers is modeled by the non-Markovian stochastic dynamics in GLE, where the memory kernel can be computed from the MD trajectories. To circumvent the difficulty in direct evaluation of the memory term and generation of colored noise, we exploit the equivalence between the non-Markovian dynamics and Markovian dynamics in an extended space. To this end, the CG system is supplemented with auxiliary variables that are coupled linearly to the momentum and among themselves, subject to uncorrelated Gaussian white noise. A high-order time-integration scheme is used to solve the extended dynamics to further accelerate the CG simulations. To assess, validate, and demonstrate the established implicit-solvent CG modeling, we have applied it to study four different types of polymers in solution. The dynamic properties of polymers characterized by the velocity autocorrelation function, diffusion coefficient, and mean square displacement as functions of time are evaluated in both CG and MD simulations. Results show that the extended dynamics with auxiliary variables can construct arbitrarily high-order CG models to reproduce dynamic properties of the reference microscopic system and to characterize long-time dynamics of polymers in solution.more » « less
-
null (Ed.)Bringing vehicle autonomy to the level of its driveline system means that the autonomous vehicle has the capability to autonomously control the distribution of power between its driving wheels. A vehicle can therefore improve mobility by autonomously redistributing wheel power. For this implementation, vehicle mobility must first be quantified by suitable mobility indices, derived from vehicle dynamics, to numerically show a wheel or vehicle is close to immobilization as well as evaluate the effect of mobility improvements on the vehicle velocity. A velocity-based mobility index combines wheel traction with velocity to maximize effectiveness of movement. Computer simulations demonstrate the potential to improve velocity by optimizing vehicle mobility of a 4x4 vehicle with a hybrid electric power transmitting unit.more » « less
-
Abstract This paper presents a hierarchical nonlinear control algorithm for the real-time planning and control of cooperative locomotion of legged robots that collaboratively carry objects. An innovative network of reduced-order models subject to holonomic constraints, referred to as interconnected linear inverted pendulum (LIP) dynamics, is presented to study cooperative locomotion. The higher level of the proposed algorithm employs a supervisory controller, based on event-based model predictive control (MPC), to effectively compute the optimal reduced-order trajectories for the interconnected LIP dynamics. The lower level of the proposed algorithm employs distributed nonlinear controllers to reduce the gap between reduced- and full-order complex models of cooperative locomotion. In particular, the distributed controllers are developed based on quadratic programing (QP) and virtual constraints to impose the full-order dynamical models of each agent to asymptotically track the reduced-order trajectories while having feasible contact forces at the leg ends. The paper numerically investigates the effectiveness of the proposed control algorithm via full-order simulations of a team of collaborative quadrupedal robots, each with a total of 22 degrees-of-freedom. The paper finally investigates the robustness of the proposed control algorithm against uncertainties in the payload mass and changes in the ground height profile. Numerical studies show that the cooperative agents can transport unknown payloads whose masses are up to 57%, 97%, and 137% of a single agent's mass with a team of two, three, and four legged robots.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
