Reversible Execution for Robustness in Embodied AI and Industrial Robots

International audienceReversible computation is a computing paradigm where execution can progress backwards as well as in the usual, forward direction. It has found applications in many areas of computer science, such as circuit design, programming languages, simulation, modelling of chemical reactions, debugging and robotics. In this article, we give an overview of reversible computation focusing on its use in robotics. We present an example of programming industrial robots for assembly operations where we combine classical AI planning with reversibility and embodied AI to increase robustness and versatility of industrial robots

Towards Interactive, Incremental Programming of ROS Nodes

Writing software for controlling robots is a complex task, usually demanding command of many programming languages and requiring significant experimentation. We believe that a bottom-up development process that complements traditional component- and MDSD-based approaches can facilitate experimentation. We propose the use of an internal DSL providing both a tool to interactively create ROS nodes and a behaviour-replacement mechanism to interactively reshape existing ROS nodes by wrapping the external interfaces (the publish/subscribe topics), dynamically controlled using the Python command line interface.Comment: Presented at DSLRob 2014 (arXiv:cs/1411.7148

Degeneracy: a design principle for achieving robustness and evolvability

Robustness, the insensitivity of some of a biological system's functionalities to a set of distinct conditions, is intimately linked to fitness. Recent studies suggest that it may also play a vital role in enabling the evolution of species. Increasing robustness, so is proposed, can lead to the emergence of evolvability if evolution proceeds over a neutral network that extends far throughout the fitness landscape. Here, we show that the design principles used to achieve robustness dramatically influence whether robustness leads to evolvability. In simulation experiments, we find that purely redundant systems have remarkably low evolvability while degenerate, i.e. partially redundant, systems tend to be orders of magnitude more evolvable. Surprisingly, the magnitude of observed variation in evolvability can neither be explained by differences in the size nor the topology of the neutral networks. This suggests that degeneracy, a ubiquitous characteristic in biological systems, may be an important enabler of natural evolution. More generally, our study provides valuable new clues about the origin of innovations in complex adaptive systems.Comment: Accepted in the Journal of Theoretical Biology (Nov 2009

A Two Dimensional Crystalline Atomic Unit Modular Self-reconfigurable Robot

Self-reconfigurable robots are designed so that they can change their external shape without human intervention. One general way to achieve such functionality is to build a robot composed of multiple, identical unit modules. If the modules are designed so that they can be assembled into rigid structures, and so that individual units within such structures can be relocated within and about the structure, then self-reconfiguration is possible. We propose the Crystalline Atomic unit modular self-reconfigurable robot, where each unit is called an Atom. In two dimensions, an Atom is square. Connectors at the faces of each Atom support structure formation (such structures are called Crystals). Centrally placed prismatic degrees of freedom give Atoms the ability to contract their outer side-length by a constant factor. By contracting and expanding groups of Atoms in a coordinated way, Atoms can relocate within and about Crystals. Thus Atoms are shown to satisfy the two properties necessary to function as modules of a self-reconfigurable robot. A powerful software simulator for Crystalline Atomic robots in two and three dimensions, called xtalsim, is presented. Xtalsim includes a high-level language interface for specifying reconfigurations, an engine which expands implicit reconfiguration plans into explicit Crystal state sequences, and an interactive animator which displays the results in a virtual environment. An automated planning algorithm for generating reconfigurations, called the Melt-Grow planner, is described. The Melt-Grow planner is fast (O(n2) for Crystals of n Atoms) and complete for a fully general subset of Crystals. The Melt-Grow planner is implemented and interfaced to xtalsim, and an automatically planned reconfiguration is simulated. Finally, the mechanics, electronics, and software for an Atom implementation are developed. Two Atoms are constructed and experiments are performed which indicate that, with some hardware improvements, an interesting self-reconfiguration could be demonstrated by a group of Atoms

Reversible Computation: Extending Horizons of Computing

This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

Timed model-based programming : executable specifications for robust mission-critical sequences

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2003.Includes bibliographical references (p. 195-204).There is growing demand for high-reliability embedded systems that operate robustly and autonomously in the presence of tight real-time constraints. For robotic spacecraft, robust plan execution is essential during time-critical mission sequences, due to the very short time available for recovery from anomalies. Traditional approaches to encoding these sequences can lead to brittle behavior under off-nominal execution conditions, due to the high level of complexity in the control specification required to manage the complex spacecraft system interactions. This work describes timed model-based programming, a novel approach for encoding and robustly executing mission-critical spacecraft sequences. The timed model-based programming approach addresses the issues of sequence complexity and unanticipated low-level system interactions by allowing control programs to directly read or write "hidden" states of the plant, that is, states that are not directly observable or controllable. It is then the responsibility of the program's execution kernel to map between hidden states and the plant sensors and control variables. This mapping is performed automatically by a deductive controller using a common-sense plant model, freeing the programmer from the error-prone process of reasoning through a complex set of interactions under a range of possible failure situations. Time is central to the execution of mission-critical sequences; a robust executive must consider time in its control and behavior models, in addition to reactively managing complexity.(cont.) In timed model-based programming, control programs express goals and constraints in terms of both system state and time. Plant models capture the underlying behavior of the system components, including nominal and off-nominal modes, probabilistic transitions, and timed effects such as state transition latency. The contributions of this work are threefold. First, a semantic specification of the timed model-based programming approach is provided. The execution semantics of a timed model-based program are defined in terms of legal state evolutions of a physical plant, represented as a factored Partially Observable Semi-Markov Decision Process. The second contribution is the definition of graphical and textual languages for encoding timed control programs and plant models. The adoption of a visual programming paradigm allows timed model-based programs to be specified and readily inspected by the systems engineers in charge of designing the mission-critical sequences. The third contribution is the development of a Timed Model-based Executive, which takes as input a timed control program and executes it, using timed plant models to track states, diagnose faults and generate control actions. The Timed Model-based Executive has been implemented and demonstrated on a representative spacecraft scenario for Mars entry, descent and landing.by Michel Donald Ingham.Sc.D

Reversible Computation: Extending Horizons of Computing

This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first