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NASA NTRS2017

Computationally Efficient Motion Planning Algorithms for Agile Autonomous Vehicles in Cluttered Environments

Fast, real-time motion planning of an agile, autonomous vehicle in a cluttered environment, with many geometrically-fixed obstacles, is a very complex problem, especially because of the vehicle dynamics constraints and resource constrained computational capabilities onboard the vehicle. In this paper, we present computationally-efficient versions of our novel motion planning algorithm called the Spherical Expansion and Sequential Convex Programming (SE–SCP) algorithm. The SE–SCP algorithm first uses a spherical-expansion-based randomized sampling algorithm to explore the workspace. Oncea path is found from the start position to the goal position, the algorithm computes a locally optimal trajectory, within its homotopy class for a desired cost function, by solving a sequence of convex optimization problems. Thus, the SE–SCP algorithm is anytime locally optimal and the trajectory is globally optimal if the number of samples tends to infinity. In this paper, we further enhance the computational efficiency of the SE–SCP algorithm using uni-directional and bi-directional rewiring techniques. We also present a detailed proof of the local optimality characteristics of the new SE–SCP algorithms for aspecial case of vehicle dynamics. Simulation examples involving quadrotor and spacecraft help demonstrate the effectiveness of our new algorithms.

Bandyopadhyay, Saptarshi↗

NASA NTRS2014

Concurrent Path Planning with One or More Humanoid Robots

A robotic system includes a controller and one or more robots each having a plurality of robotic joints. Each of the robotic joints is independently controllable to thereby execute a cooperative work task having at least one task execution fork, leading to multiple independent subtasks. The controller coordinates motion of the robot(s) during execution of the cooperative work task. The controller groups the robotic joints into task-specific robotic subsystems, and synchronizes motion of different subsystems during execution of the various subtasks of the cooperative work task. A method for executing the cooperative work task using the robotic system includes automatically grouping the robotic joints into task-specific subsystems, and assigning subtasks of the cooperative work task to the subsystems upon reaching a task execution fork. The method further includes coordinating execution of the subtasks after reaching the task execution fork.

Sanders, Adam M.↗

NASA NTRS2014

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance

Experimentation↗

NASA NTRS1989

The KALI multi-arm robot programming and control environment

The KALI distributed robot programming and control environment is described within the context of its use in the Jet Propulsion Laboratory (JPL) telerobot project. The purpose of KALI is to provide a flexible robot programming and control environment for coordinated multi-arm robots. Flexibility, both in hardware configuration and software, is desired so that it can be easily modified to test various concepts in robot programming and control, e.g., multi-arm control, force control, sensor integration, teleoperation, and shared control. In the programming environment, user programs written in the C programming language describe trajectories for multiple coordinated manipulators with the aid of KALI function libraries. A system of multiple coordinated manipulators is considered within the programming environment as one motion system. The user plans the trajectory of one controlled Cartesian frame associated with a motion system and describes the positions of the manipulators with respect to that frame. Smooth Cartesian trajectories are achieved through a blending of successive path segments. The manipulator and load dynamics are considered during trajectory generation so that given interface force limits are not exceeded.

Backes, Paul↗

NASA NTRS1991

Path planning algorithms for assembly sequence planning

Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.

Krishnan, S. S.↗

NASA NTRS1990

The JPL/KSC telerobotic inspection demonstration

An ASEA IRB90 robotic manipulator with attached inspection cameras was moved through a Space Shuttle Payload Assist Module (PAM) Cradle under computer control. The Operator and Operator Control Station, including graphics simulation, gross-motion spatial planning, and machine vision processing, were located at JPL. The Safety and Support personnel, PAM Cradle, IRB90, and image acquisition system, were stationed at the Kennedy Space Center (KSC). Images captured at KSC were used both for processing by a machine vision system at JPL, and for inspection by the JPL Operator. The system found collision-free paths through the PAM Cradle, demonstrated accurate knowledge of the location of both objects of interest and obstacles, and operated with a communication delay of two seconds. Safe operation of the IRB90 near Shuttle flight hardware was obtained both through the use of a gross-motion spatial planner developed at JPL using artificial intelligence techniques, and infrared beams and pressure sensitive strips mounted to the critical surfaces of the flight hardward at KSC. The Demonstration showed that telerobotics is effective for real tasks, safe for personnel and hardware, and highly productive and reliable for Shuttle payload operations and Space Station external operations.

Mittman, David↗

NASA NTRS2000

Reaching during virtual rotation: context specific compensations for expected coriolis forces

Subjects who are in an enclosed chamber rotating at constant velocity feel physically stationary but make errors when pointing to targets. Reaching paths and endpoints are deviated in the direction of the transient inertial Coriolis forces generated by their arm movements. By contrast, reaching movements made during natural, voluntary torso rotation seem to be accurate, and subjects are unaware of the Coriolis forces generated by their movements. This pattern suggests that the motor plan for reaching movements uses a representation of body motion to prepare compensations for impending self-generated accelerative loads on the arm. If so, stationary subjects who are experiencing illusory self-rotation should make reaching errors when pointing to a target. These errors should be in the direction opposite the Coriolis accelerations their arm movements would generate if they were actually rotating. To determine whether such compensations exist, we had subjects in four experiments make visually open-loop reaches to targets while they were experiencing compelling illusory self-rotation and displacement induced by rotation of a complex, natural visual scene. The paths and endpoints of their initial reaching movements were significantly displaced leftward during counterclockwise illusory rotary displacement and rightward during clockwise illusory self-displacement. Subjects reached in a curvilinear path to the wrong place. These reaching errors were opposite in direction to the Coriolis forces that would have been generated by their arm movements during actual torso rotation. The magnitude of path curvature and endpoint errors increased as the speed of illusory self-rotation increased. In successive reaches, movement paths became straighter and endpoints more accurate despite the absence of visual error feedback or tactile feedback about target location. When subjects were again presented a stationary scene, their initial reaches were indistinguishable from pre-exposure baseline, indicating a total absence of aftereffects. These experiments demonstrate that the nervous system automatically compensates in a context-specific fashion for the Coriolis forces associated with reaching movements.

Clinical Trial↗

NASA NTRS2014

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

Dynamic environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal paths through these environments. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially with the number of agents in the system. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance.

Coevolution↗

NASA NTRS1988

Collision detection for planning collision-free motion of two robot arms

The authors focus on collision detection for planning collision-free motion of two robot arms in a common workspace. A collision-free motion is obtained by detecting collisions along the straight-line trajectories of the robots using a sphere model for the wrists and then replanning the paths and/or trajectories of one or both of the robots to avoid collisions. A novel approach to collision detection is presented and a discussion on collision avoidance is given.

Basta, Robert A.↗

NASA NTRS2010

Graph-Based Path-Planning for Titan Balloons

A document describes a graph-based path-planning algorithm for balloons with vertical control authority and little or no horizontal control authority. The balloons are designed to explore celestial bodies with atmospheres, such as Titan, a moon of Saturn. The algorithm discussed enables the balloon to achieve horizontal motion using the local horizontal winds. The approach is novel because it enables the balloons to use arbitrary wind field models. This is in contrast to prior approaches that used highly simplified wind field models, such as linear, or binary, winds. This new approach works by discretizing the space in which the balloon operates, and representing the possible states of the balloon as a graph whose arcs represent the time taken to move from one node to another. The approach works with arbitrary wind fields, by looking up the wind strength and direction at every node in the graph from an arbitrary wind model. Having generated the graph, search techniques such as Dijkstra s algorithm are then used to find the set of vertical actuation commands that takes the balloon from the start to the goal in minimum time. In addition, the set of reachable locations on the moon or planet can be determined.

Blackmore, Lars James↗

NASA NTRS1991

Experiments in robotic catching

Real-time coordination of visual information with high-speed manipulator control is studied in the context of three-dimensional robotic catching. All path planning for the catch occurs in real-time during the half-second that the targeted object is airborne. A trajectory-matching algorithm is used that combines an observer with a varying-strength filter, an error estimator, and an initial motion algorithm. The results are demonstrated experimentally using a real-time vision system and a four-degree-of-freedom, cable-driven arm with a workspace of 4.2 m3 and speed capabilities of up to 2.0 m/s.

Hove, Barbara↗

NASA NTRS1989

Kinematics, controls, and path planning results for a redundant manipulator

The inverse kinematics solution, a modal position control algorithm, and path planning results for a 7 degree of freedom manipulator are presented. The redundant arm consists of two links with shoulder and elbow joints and a spherical wrist. The inverse kinematics problem for tip position is solved and the redundant joint is identified. It is also shown that a locus of tip positions exists in which there are kinematic limitations on self-motion. A computationally simple modal position control algorithm has been developed which guarantees a nearly constant closed-loop dynamic response throughout the workspace. If all closed-loop poles are assigned to the same location, the algorithm can be implemented with very little computation. To further reduce the required computation, the modal gains are updated only at discrete time intervals. Criteria are developed for the frequency of these updates. For commanding manipulator movements, a 5th-order spline which minimizes jerk provides a smooth tip-space path. Schemes for deriving a corresponding joint-space trajectory are discussed. Modifying the trajectory to avoid joint torque saturation when a tip payload is added is also considered. Simulation results are presented.

Gretz, Bruce↗

NASA NTRS2002

On the validity of the double integrator approximation in deep space formation flying

Free-flying models are commonly used f o r path planning and open loop control design (i. e., guidance design) and translational feedback control design (i. e., control design) for deep space precision formation flying. The free flying model, essentially a double integrator, results from discarding small terms in the relative spacecraft equations of motion. While the magnitude of these discarded terms may be small, one must show that their dynamic effects are small as compared to the precision performance requirements. We do so by deriving a theoretical method for bounding the difference between the solution of a nonlinear truth model of the relative translational spacecraft dynamics and a Simplified linear time-invariant model. Presently, the method incorporates feedforward and static output feedback control. The method is applied to a Terrestrial Planet Finder- based example. Using only feedforward control (guidance) the free-flying model and a Hill- Clohessy- Wiltshire Equations-based model are shown to be accurate to 1 c m for up to 4 and 30 hours, respectively. Also shown is that the simplest free-flying model may not be sufficient for low-gain feedback control design-closed-loop tracking errors can be as large as 8 meters.

formation flying free flying model double integrat↗

NASA NTRS1989

Trajectory generation of space telerobots

The purpose is to review a variety of trajectory generation techniques which may be applied to space telerobots and to identify problems which need to be addressed in future telerobot motion control systems. As a starting point for the development of motion generation systems for space telerobots, the operation and limitations of traditional path-oriented trajectory generation approaches are discussed. This discussion leads to a description of more advanced techniques which have been demonstrated in research laboratories, and their potential applicability to space telerobots. Examples of this work include systems that incorporate sensory-interactive motion capability and optimal motion planning. Additional considerations which need to be addressed for motion control of a space telerobot are described, such as redundancy resolution and the description and generation of constrained and multi-armed cooperative motions. A task decomposition module for a hierarchical telerobot control system which will serve as a testbed for trajectory generation approaches which address these issues is also discussed briefly.

Lumia, R.↗

NASA NTRS1992

Robot path planning for space-truss assembly

Construction, repair, and maintenance of space-based structures will require extensive planning of operations in order to effectively carry out these tasks. The path planning algorithm described here is a general approach to generating paths that guarantee collision avoidance for a single chain nonredundant or redundant robot. The algorithm uses a graph search of feasible points in position space, followed by a local potential field method that guarantees collision avoidance among objects, structures, and the robot arm as well as conformance to joint limit constraints. This algorithm is novel in its computation of goal attractive potential fields in Cartesian space, and computation of obstacle repulsive fields in robot joint space. These effects are combined to generate robot motion. Computation is efficiently implemented through the computation of the robot arm Jacobian and not the full inverse arm kinematics. These planning algorithms have been implemented and evaluated using existing space-truss designs, and are being integrated into the RPI-CIRSSE Testbed environment.

Muenger, Rolf↗

NASA NTRSDate not supplied

Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft

This paper presents a comparison of trajectory generation methodologies using acoustic source noise models of different fidelity for motion planning for an acoustically-aware aircraft subject to constraints on the vehicle dynamic performance, mission, and acoustic footprint of the vehicle at a set of (three-dimensional) observer locations. The performance of a pre-mission Bézier curve-based planner and a (near) real-time stochastic model predictive control planner are compared. Additionally, a comparison is made between the motion planning performance using a lower-fidelity acoustic model based on propeller tip Mach number and omni-directional sound power radiation, and a hemisphere-based higher-fidelity acoustic model. It is demonstrated that the asymmetry in hemisphere-based acoustic model can be exploited for improved flight path planning and trajectory-tracking performance in the presence of acoustic constraints.

Kasey A Ackerman↗

NASA NTRS2017

Distributed Fast Motion Planning for Spacecraft Swarms in Cluttered Environments using Spherical Expansions and Sequence of Convex Optimization Problems

This paper presents a novel guidance algorithm for spacecraft swarms in an environment cluttered with many obstacles like a debris field or the asteroid belt. The objective of this algorithm is to reconfigure the swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with the obstacles. The agents first use a spherical-expansion-based sampling algorithm to cooperatively explore the workspace and find paths to the desired terminal positions. Using a distributed assignment algorithm, the agents converge on an optimal assignment of the target locations in the desired formation. Then each agent generates a locally optimal trajectory from its current location to its terminal position by solving a sequence of convex optimization problems. As the agent moves along this trajectory, it receives the position of other agents and updates its trajectory to avoid collisions with other agents and the obstacles. Thus the swarm achieves the desired formation in a distributed manner while avoiding collisions. Moreover, this algorithm is computationally efficient, therefore it can be implemented onboard resource-constrained spacecraft. Simulations results show that the proposed distributed algorithm can be used by a spacecraft swarm to reconfigure a desired formation around an asteroid in a collision-free manner.

Bandyopadhyay, Saptarshi↗

NASA NTRS1988

Motion planning for a free-flying robot

An investigation is presented of motion planning combining low level control and obstacle avoidance for a free flying robot. This free flying robot is an outgrowth of the concept of an assistant for astronauts on the U.S. Space Station and Shuttle. A motion planner based on the Khatib potential field approach is described. Because of the uncluttered environment in space, it generates a path from representation of known obstacles rather than from a representation of free space. A global planner supplies the low level controller with interim points between the current position and the desired goal position so that the vehicle does not become trapped by local minima, a phenomenon of the potential field approach. Discussion of the feasibility of this system for space applications is presented.

Kaiser, Donald Leo↗