Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation

A generic computer simulation for manipulator systems (ROBSIM) was implemented and the specific technologies necessary to increase the role of automation in various missions were developed. The specific items developed are: (1) capability for definition of a manipulator system consisting of multiple arms, load objects, and an environment; (2) capability for kinematic analysis, requirements analysis, and response simulation of manipulator motion; (3) postprocessing options such as graphic replay of simulated motion and manipulator parameter plotting; (4) investigation and simulation of various control methods including manual force/torque and active compliances control; (5) evaluation and implementation of three obstacle avoidance methods; (6) video simulation and edge detection; and (7) software simulation validation

Real-Time Optimal Slew Maneuver Planning for Small Satellites

As the small-satellite market grows, so does the demand for large-scale small-satellite missions with diverse payload functions. To facilitate mission planning, and to enable autonomous transition between payload operations, real-time on-board slew maneuver path planning is often required to reorient the spacecraft. The computed trajectory must take into account a variety of kinematic and dynamic constraints on the spacecraft attitude, angular velocity and actuator limits. It is also desirable to compute this trajectory such that it is optimal in some sense. To simplify computation, current applications typically employ a “rest-to-rest” assumption where the maneuver endpoints are assumed to be inertially fixed, leading to long settling times in practice when dynamic endpoints exist. This settling time prohibits command of maneuvers in quick succession, which can limit operational capabilities. By posing the calculation as a convex semidefinite programming optimization problem, this paper presents a computationally attractive path-planning algorithm that computes an optimal fixed-time trajectory between arbitrary endpoints, while satisfying a variety of common attitude control constraints. In addition, a closed-form iterative solution for a minimum-time maneuver is proposed. Both methods are validated in a simulation case involving the University of Toronto Institute for Aerospace Studies Space Flight Laboratory’s (UTIAS-SFL) next-generation DEFIANT-class spacecraft

Shuttle tethered operations: The effect on orbital trajectory and inertial navigation

The first full scale test of a large tethered satellite system is planned. The Orbiter will be linked to a 500 kg payload by a 20 km tether, an action with a profound effect on the trajectory of the Orbiter. For the first time in the history of the Shuttle program, the vehicle will conduct prolonged operations with the center of mass of the orbiting system a significant distance from the center of mass of the Space Shuttle Orbiter, a violation of the fundamental assumption made in both the Orbiter ground-based and onboard navigation software. Inertial navigation of tethered operations with the Shuttle is further complicated by the presence of non-conservative forces in the system: Reaction Control System (RCS) translational effects, atmospheric drag, and electro-magnetic dynamics. These can couple with the conservative tether dynamics effects, and degrade the navigation software performance. The primary effects are examined on the Orbiter's trajectory, coupling by conservative forces during tethered operations, and the impact of both on the ability to meet inertial navigation constraints. The impact of electrodynamics, different RCS control modes, commanded attitudes, and attitude deadbands are presented. Operational guidelines which optimize successful mission navigation, and necessary navigation constraints are discussed

Autonomous Hybrid Ground/Aerial Mobility in Unknown Environments

Hybrid ground and aerial vehicles can possess distinct advantages over ground-only or flight-only designs in terms of energy savings and increased mobility. In this work we outline our unified framework for controls, planning, and autonomy of hybrid ground/air vehicles. Our contribution is three-fold: 1) We develop a control scheme for the control of passive two-wheeled hybrid ground/aerial vehicles. 2) We present a unified planner for both rolling and flying by leveraging differential flatness mappings. 3) We conduct experiments leveraging mapping and global planning for hybrid mobility in unknown environments, showing that hybrid mobility uses up to five times less energy than flying only

Perception-aware time optimal path parameterization for quadrotors

The increasing popularity of quadrotors has given rise to a class of predominantly vision-driven vehicles. This paper addresses the problem of perception-aware time optimal path parametrization for quadrotors. Although many different choices of perceptual modalities are available, the low weight and power budgets of quadrotor systems makes a camera ideal for on-board navigation and estimation algorithms. However, this does come with a set of challenges. The limited field of view of the camera can restrict the visibility of salient regions in the environment, which dictates the necessity to consider perception and planning jointly. The main contribution of this paper is an efficient time optimal path parametrization algorithm for quadrotors with limited field of view constraints. We show in a simulation study that a state-of-the-art controller can track planned trajectories, and we validate the proposed algorithm on a quadrotor platform in experiments.Comment: Accepted to appear at ICRA 202

Smooth trajectory generation for rotating extensible manipulators

In this study the generation of smooth trajectories of the end-effector of a rotating extensible manipulator arm is considered. Possible trajectories are modelled using Cartesian and polar piecewise cubic interpolants expressed as polynomial Hermite-type functions. The use of polar piecewise cubic interpolants devises continuous first and - in some cases - second order derivatives and allows easy calculation of kinematics variables such as velocity and acceleration. Moreover, the manipulator equations of motion can be easily handled, and the constrained trajectory of the non-active end of the manipulator derived directly from the position of the end-effector. To verify the proposed approach, numerical simulations are conducted for two different configurations

Trajectory Generation for a Multibody Robotic System: Modern Methods Based on Product of Exponentials

This work presents several trajectory generation algorithms for multibody robotic systems based on the Product of Exponentials (PoE) formulation, also known as screw theory. A PoE formulation is first developed to model the kinematics and dynamics of a multibody robotic manipulator (Sawyer Robot) with 7 revolute joints and an end-effector. In the first method, an Inverse Kinematics (IK) algorithm based on the Newton-Raphson iterative method is applied to generate constrained joint-space trajectories corresponding to straight-line and curvilinear motions of the end effector in Cartesian space with finite jerk. The second approach describes Constant Screw Axis (CSA) trajectories which are generated using Machine Learning (ML) and Artificial Neural Networks (ANNs) techniques. The CSA method smooths the trajectory in the Special Euclidean (SE(3)) space. In the third approach, a multi-objective Swarm Intelligence (SI) trajectory generation algorithm is developed, where the IK problem is tackled using a combined SI-PoE ML technique resulting in a joint trajectory that avoids obstacles in the workspace, and satisfies the finite jerk constraint on end-effector while minimizing the torque profiles. The final method is a different approach to solving the IK problem using the Deep Q-Learning (DQN) Reinforcement Learning (RL) algorithm which can generate different joint space trajectories given the Cartesian end-effector path. For all methods above, the Newton-Euler recursive algorithm is implemented to compute the inverse dynamics, which generates the joint torques profiles. The simulated torque profiles are experimentally validated by feeding the generated joint trajectories to the Sawyer robotic arm through the developed Robot Operating System (ROS) - Python environment in the Software Development Kit (SDK) mode. The developed algorithms can be used to generate various trajectories for robotic arms (e.g. spacecraft servicing missions)