1
|
Nesnas IAD, Hockman BJ, Bandopadhyay S, Morrell BJ, Lubey DP, Villa J, Bayard DS, Osmundson A, Jarvis B, Bersani M, Bhaskaran S. Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions. Front Robot AI 2021; 8:650885. [PMID: 34790702 PMCID: PMC8592236 DOI: 10.3389/frobt.2021.650885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 08/09/2021] [Indexed: 11/25/2022] Open
Abstract
Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodies as a key functional capability for an autonomous small-body explorer. We use a multi-phase perception/estimation pipeline with interconnected and overlapping measurements and algorithms to characterize and reach the body, from millions of kilometers down to its surface. We consider a notional spacecraft design that operates across all phases from approach to landing and to maneuvering on the surface of the microgravity body. This SmallSat design makes accommodations to simplify autonomous surface operations. The estimation pipeline combines state-of-the-art techniques with new approaches to estimating the target’s unknown properties across all phases. Centroid and light-curve algorithms estimate the body–spacecraft relative trajectory and rotation, respectively, using a priori knowledge of the initial relative orbit. A new shape-from-silhouette algorithm estimates the pole (i.e., rotation axis) and the initial visual hull that seeds subsequent feature tracking as the body gets more resolved in the narrow field-of-view imager. Feature tracking refines the pole orientation and shape of the body for estimating initial gravity to enable safe close approach. A coarse-shape reconstruction algorithm is used to identify initial landable regions whose hazardous nature would subsequently be assessed by dense 3D reconstruction. Slope stability, thermal, occlusion, and terra-mechanical hazards would be assessed on densely reconstructed regions and continually refined prior to landing. We simulated a mission scenario for approaching a hypothetical small body whose motion and shape were unknown a priori, starting from thousands of kilometers down to 20 km. Results indicate the feasibility of recovering the relative body motion and shape solely relying on onboard measurements and estimates with their associated uncertainties and without human input. Current work continues to mature and characterize the algorithms for the last phases of the estimation framework to land on the surface.
Collapse
Affiliation(s)
- Issa A D Nesnas
- Mobility and Robotics Systems Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Benjamin J Hockman
- Mobility and Robotics Systems Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Saptarshi Bandopadhyay
- Mobility and Robotics Systems Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Benjamin J Morrell
- Mobility and Robotics Systems Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Daniel P Lubey
- Mission Design and Navigation Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Jacopo Villa
- Ann and H.J. Smead Aerospace Engineering Sciences Department, University of Colorado Boulder, Boulder, CO, United States
| | - David S Bayard
- Guidance and Control Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| | - Alan Osmundson
- University of Southern California, Los Angeles, CA, United States
| | | | | | - Shyam Bhaskaran
- Mission Design and Navigation Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
| |
Collapse
|
2
|
Diaz-Calderon A, Nesnas IAD, Nayar HD, Kim WS. Towards a Unified Representation of Mechanisms for Robotic Control Software. INT J ADV ROBOT SYST 2006. [DOI: 10.5772/5757] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
This article gives an overview of the Mechanism Model paradigm. The mechanism model paradigm provides a framework to modeling mechanisms for robotic control. The emphasis is on the unification of mathematical models of kinematics/dynamics, geometric information and control system parameters for a variety of robotic systems (including serial manipulators, wheeled and legged locomotors), with algorithms that are needed for typical robot control applications.
Collapse
Affiliation(s)
| | - Issa A. D. Nesnas
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | - Won S. Kim
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| |
Collapse
|