Search results for: Matthias Althoff
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We address the problem of overapproximative short-term prediction of arm movement, for safe human-robot co-existence. A trajectory planner for a robot manipulator which formally verifies non-collision requires fast prediction of human future occupancy, which must be accurate yet still account for all possible human movement. This work presents two approaches to this: a novel, simple approach calculated...
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Mobile robots operating in a shared environment with pedestrians are required to move provably safe to avoid harming pedestrians. Current approaches like safety fields use conservative obstacle models for guaranteeing safety, which leads to degraded performance in populated environments. In this paper, we introduce an online verification approach that uses information about the current pedestrian...
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Commercially available robots cannot always be adapted to arbitrary tasks or environments, particularly when the task would exceed the kinematic or dynamic limits of the robot. Modular robots offer a solution to this problem, since they can be reconfigured in various ways from a set of modules. The challenge of choosing the optimal composition for a given task, however, is hard since the search space...
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2017 IEEE Intelligent Vehicles Symposium (IV) > 719 - 726
Numerical experiments for motion planning of road vehicles require numerous components: vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement over time, goal regions, a cost function, etc. Providing a description of the numerical experiment precise enough to reproduce it might require several pages of information. Thus, only key aspects are typically described in...
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2017 IEEE Intelligent Vehicles Symposium (IV) > 1477 - 1483
Validating the safety of self-driving vehicles requires an enormous amount of testing. By applying formal verification methods, we can prove the correctness of the vehicles' behavior, which at the same time reduces remaining risks and the need for extensive testing. However, current safety approaches do not consider liabilities of traffic participants if a collision occurs. Utilizing formalized traffic...
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2017 IEEE Intelligent Vehicles Symposium (IV) > 1686 - 1693
Predicting the movement of other traffic participants is an integral part in the motion planning of most automated road vehicles. While simple predictions, e.g. based on assuming constant velocity, may suffice for deciding a driving strategy, predicting the set of all possible behaviors is required to ensure safe motion plans. In this work, we propose a novel tool for the latter problem based on reachability...
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2017 IEEE Intelligent Vehicles Symposium (IV) > 647 - 654
We introduce a novel concept based on maneuver templates, which are formalized collaborative maneuvers, to select cooperative driving strategies. The approach is based on the exclusion principle, where we derive provable conditions to discard unsafe cooperative maneuvers for a given traffic situation. We thereby consider the full action set of all cooperative vehicles and do not discretize the action...
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2017 IEEE Intelligent Vehicles Symposium (IV) > 160 - 166
Motion planing in dynamic traffic scenes is a challenging problem. In particular, since it is unknown during planning whether a certain decision, such as passing another traffic participant on the left or right, will result in a safe and comfortable motion. Exhaustive exploration of all principle driving paths is computationally expensive, so that one typically reverts to heuristics — this, however...
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We consider the global tracking control problem of robots with elastic joints. Even if joint elasticity introduces beneficial features for modern applications which require physically resilient and safer robots that can interact with the environment or humans, it challenges the achievable control performance. We propose a novel controller which combines the benefits of two approaches: the intrinsic...
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We propose and implement an algorithm based on reachability analysis to estimate the region of attraction (ROA) of an equilibrium point for nonlinear systems. The stability region is obtained via the computation of forward reachable sets. We compare our results with well-established techniques in this area. In particular, we consider the optimization of the Lyapunov function (LF) sub-level set using...
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Optimal control finds an optimal input trajectory which steers an initial state to a desired final state while satisfying given state and input constraints. However, most efficient approaches are restricted to a single initial state. In this paper, we present a new approach, which combines reachability analysis with optimal control. This enables us to solve the optimal control problem for a whole...
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The main challenge associated with the analysis of power systems via the computation of reachable sets is improving the algorithmic efficiency to scale towards industrially relevant problem sizes. In this paper, we present a compositional algorithm that can drastically reduce the computational effort required to assess the dynamical response of power systems during transients using reachability analysis...
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We propose a method for efficient numerical computation of interval-arithmetic-based robust controllers for rigid robot manipulators. The use of interval arithmetic for robust control is the core of a recently proposed approach which allows a user-defined tracking performance to be ultimately met despite uncertain models and input disturbance, without requiring an empirical estimation of bounds of...
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2016 IEEE 55th Conference on Decision and Control (CDC) > 5569 - 5576
Estimating the domain of attraction (DA) of an equilibrium point is a long-standing yet still challenging issue in nonlinear system analysis. The method using the sublevel set of Lyapunov functions is proven to be efficient, but sometimes conservative compared to the estimate via invariant sets. This paper studies the estimation problem of the DA for autonomous polynomial system by using the invariance...
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2016 IEEE 55th Conference on Decision and Control (CDC) > 7439 - 7446
Reachability analysis is an important technique for formally verifying continuous systems, as well as for guaranteed state estimation, stability analysis, and controller synthesis. We present a detailed assessment of the computational efficiency for the reachability analysis of linear systems with respect to the two most scalable set representations: zonotopes and support functions. As a result, we...
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2016 IEEE 55th Conference on Decision and Control (CDC) > 2176 - 2183
An increasingly important issue in the area of uncertain systems is the estimation of the Robust Domain of Attraction (RDA). Though this topic is of great interest, most of attention has been paid to the RDA for uncertain polynomial systems. This paper considers the RDA for rational polynomial systems and non-polynomial systems, both with parametric uncertainties, which are constrained in a semialgebraic...
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A frequently raised argument against safely-driving automated vehicles is that they would not harmonize well with traffic flow—unrealistically large headways would invite other traffic participants to cut in and thus put passengers of following automated vehicles at risk. In order to test this hypothesis, we use real data of thousands of vehicles recorded in the United States as part of the Next Generation...
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IEEE Transactions on Power Systems > 2016 > 31 > 6 > 4691 - 4702
The load-following capabilities of power plants became increasingly important in recent years as a means of ensuring a reliable operation of future power systems. In this work, we propose a generic approach, based on reachability analysis, to rigorously verify the safety of critical components that often pose limitations on the flexibility of conventional power plants to perform fast load changes...
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Formally verified methods for motion planning are required in order to guarantee safety for autonomous vehicles. In particular, we consider trajectory generation by considering the most probable trajectory of other traffic participants. However, if the surrounding vehicles perform unexpected maneuvers, a collision might be inevitable. In this paper, a fail-safe motion planner is developed, which generates...
