A key challenge to the widespread deployment of robotic manipulators is the need to ensure safety in arbitrary environments while generating new motion plans in real-time. In particular, one must ensure that a manipulator does not collide with obstacles, collide with itself, or exceed its joint torque limits. This challenge is compounded by the need to account for uncertainty in the mass and inertia of manipulated objects, and potentially the robot itself. The present work addresses this challenge by proposing Autonomous Robust Manipulation via Optimization with Uncertainty-aware Reachability (ARMOUR), a provably-safe, receding-horizon trajectory planner and tracking controller framework for serial link manipulators. ARMOUR works by first constructing a robust, passivity-based controller that is proven to enable a manipulator to track desired trajectories with bounded error despite uncertain dynamics. Next, ARMOUR uses a novel variation on the Recursive Newton-Euler Algorithm (RNEA) to compute the set of all possible inputs required to track any trajectory within a continuum of desired trajectories. Finally, the method computes an over-approximation to the swept volume of the manipulator; this enables one to formulate an optimization problem, which can be solved in realtime, to synthesize provably-safe motion. The proposed method is compared to state of the art methods and demonstrated on a variety of challenging manipulation examples in simulation and on real hardware, such as maneuvering a dumbbell with uncertain mass around obstacles.
We propose a novel approach and tool for collaborative software engineering and development. In model-based software engineering, the underlying data structure is a complex, directed and labeled graph. Collaborative engineering requires that developers be able to copy the graph, make independent changes, compare them, detect conflicts, and merge nonconflicting graphs. To support different collaboration and development styles requires a very flexible toolset. Worldwide, loosely-coupled development teams require the support of large-scale networks of users, possibly disconnected, in a decentralised fashion. No matter how the graph replicas evolve, they must eventually converge. We describe and evaluate C-Praxis, a tool that satisfies these requirements.
By considering an essential subset of the BPEL orchestration language, we define SeB, a session based style of this subset. We discuss the formal semantics of SeB and we present its main properties. We use a new approach to address the formal semantics, based on a translation into so-called control graphs. Our semantics handles control links and addresses the static semantics that prescribes the valid usage of variables. We also provide the semantics of collections of networked services. Relying on these semantics, we define precisely what is meant by interaction safety, paving the way to the formal analysis of safe interactions between BPEL services
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.