t Bench for Robotics and Autonomy Andrea Merlo

Transcription

1 t Bench for Robotics and Autonomy Andrea Merlo

2 Agenda Introduction TBRA Overview Objectives Architecture / Technical Description Status Test Results Roadmap

3 he context of a Rover, dance, Navigation and trol (GNC) is the bined process of ermining a path to be owed, determining ation relative to the ired path and exerting trol to reduce the erence between the ual and desired path h in position and ding. These three ks are called igation, Localisation Trajectory Control Introduction

4 TBRA Overview TBRA relies on two fundamental and innovative aspects in the robotics domain Flexibility Achieved by the definition of a modular software architecture in which each module provides a key functionality of the Guidance, Navigation and Control System (e.g. navigation, locomotion, localisation) Modularity Resulting from the standardization of the interfaces and data structures exchanged between the software modules This is in contrast with the established concept of ad-hoc development typical of the space applications domain

5 Technological Objectives Development of a Software Framework Modular Flexible Scalable Portable Distributed With Standardized Interfaces for Data Exchange Development of a Mobile Robotic Platform With Integrated GNC Sensors Capable of Indoor and Outdoor Autonomous Navigation Capable of Interact with the Environment

6 Strategic Objectives Acquisition of competences and experience in all the robotics domains related to Space Exploration Team Growth Design and development of new solutions for the Space Market Nevermore start from scratch Support to programs, project and studies development Anticipate Space Market (future exploration missions) needs Innovative Sensors (Omnicamera, Time-of-flight Camera, ) Robot Swarms Manipulation Samples Fetching and Handling Opportunistic Science Reactive Navigation Simultaneous Localization and mapping (SLAM) Validation and Testing of GNC Algorithms

7 Functional Overview

8 Architecture

9 Architecture: Command Chain

10 Rover HW Configuration

11 Rover Functional Configuration

12 TBRA Advantages 1/2 Eases the development of Real-Time GNC algorithms Manages transparently all the issues related to: Inter-task communication (even remotely over network) Real-time requirements Interfacing with the physical system (robot) Allowing the developer to focus on the algorithmic part Eases the porting on different platforms Kernel Abstraction Layer (KAL) for easy porting on different OS Hardware Abstraction Layer (HAL) for easy porting on different Robots In-House Testing and Validation At cost of a little overhead in processing power and memory

13 TBRA Advantages 2/2 Each module can be developed and tested as a separate (standalone) entity Then it can be easily enclosed in the TBRA with minimal coding effort and tested within the existing system This results in Time saving Almost 1:1 porting from the standalone application to the TBRA SW module Remote modules differ from the local module by a single line of code Software reuse Changing a module, algorithm or subsystem does not affect the whole system architecture or implementation Hardware Modularity Adding or removing a piece of hardware (sensor, actuator, etc ) results only in adding or removing a SW module from the architecture

14 Current Status Software Infrastructure Framework: complete for Linux/RTAI Kernel Abstraction Layer: Assessment Completed (currently under implementation) Hardware Abstraction Layer: complete for current robot (minor changes for next procured robotic platform) Functional Modules: complete (further improvement, optimization and testing foreseen) Autonomy Module: baseline implementation (further development and testing foreseen) Rover Capable of Autonomous Navigation in Indoor and Outdoor Environments All the procured GNC sensors have been integrated and exploited New GNC sensors (Omnicamera, Time-of-Flight Camera) and 6DOF Manipulator under procurement

15 TBRA Testing Open Loop Testing Navigation Perception tion Traversability Navigation Path Planning sation Visual Odometry

16 TBRA Testing Closed Loop Testing Autonomous Navigation

17 Short Term Plan ( ) 11 Planned Activities: Porting of TBRA Framework on RTEMS OS and Flight Hardware KAL Implementation and Preliminary Testing Development of New Modules for Innovative GNC Sensors Simultaneous Localization And Mapping (SLAM) with Omnicamera 3D Map Reconstruction with Laser Time-of-Flight (ToF) Camera Baseline Manipulator module for 6DOF Arm Improvement of Existing Modules Procurement and Setup of a New Mobile Robotic Platform Study of Robot Swarms, Object Recognition, Mission and Action Planning Strengthening of collaborations with universities

18 Short Term Plan ( ) 12 Foreseen Activities: Consolidation of TBRA on RTEMS OS and Flight Hardware Extensive Testing of TBRA Framework Porting / Development and Testing of TBRA Functional Modules Robot Swarms Development and Testing of Coordination and Collaboration between real and simulated robots Manipulation Baseline Visual Servoing Baseline Sample Fetching and Handling Target Tracking Development of New Modules for Innovative GNC Sensors Simultaneous Localization And Mapping (SLAM) with Omnicamera 3D Map Reconstruction with Laser Time-of-Flight (ToF) Camera Baseline Manipulator module for 6DOF Arm

19 Medium/Long Term Plan ( ) 013+ Objectives: Autonomously Operative Heterogeneous Robot Swarm (at least 3 robots) Procurement and Setup of a Flight-Hardware Based Robotic Platform Exploit TBRA advantages in ongoing and future programs Team and Competences Growth 013+ Research Streams: Robot Swarms Sample Fetching and Handling Autonomy, Mission and Action Planning / Re-planning Innovative GNC Algorithms and Strategies Innovative Sensors and Actuators

20 Programs / Projects / Studies Heritage ExoMars mission, Phase A, B1, B2 NEXT MOON Ongoing XROB, ESA Study: Closed-loop testing of the Visual Odometry algorithm Closed-loop testing of the Localisation Data Fusion algorithm STEPS, Piedmont Region Project Support to the development and testing of Localization and Perception algorithms Closed-loop testing of Localization and Perception algorithms Future ExoMars Mars Sample Return (MSR) DELIAN Eurobot Ground Prototype (EGP)

21 Summary HAT IS TBRA? is an architecture for development and testing of innovative GNC algorithms is based on a Flexible and Modular framework is capable of Autonomous Navigation each module is a self-standing Plug & Play SW entity eases the development and testing process HAT CAN I DO WITH TBRA? Functional Verificator of GNC algorithms for performance evaluation, optimization and open/closed loop testing, necessary during proposal and A & B project phases; Test Bench for development of new GNC algorithms based on new GNC sensors (Omni-cameras, TOF cameras, 3D Laser Scanner), suitable for space applications; Soon Test Bench composed by 2 cooperating robots for robot swarms studies.

22 Questions?