The workspace of a robot can be restricted by virtual fixtures to assist an operator in physical human-robot interaction tasks. This paper introduces a combination of surface following control (SFC) with compliance control and presents a path/SFC approach to systematically generate virtual fixtures. This approach allows implementation of numerous types of constraints like guidance and forbidden region virtual fixtures, hard and soft constraints, as well as static and dynamic virtual fixtures, and their combinations. Additionally, closed-loop stability proofs of the proposed control concepts are given. The flexibility of the presented approach is demonstrated by a series of measurement results from an industrial robot.

This paper presents a path planning concept for trucks with trailers with kingpin hitching. This system is nonholonomic, has no flat output and is not stable in backwards driving direction. These properties are major challenges for path planning. The presented approach concentrates on the loading bay scenario. The considered task is to plan a path for the truck-trailer system from a start to a specified target configuration corresponding to the loading bay. Thereby, close distances to obstacles and multiple driving direction changes have to be handled. Furthermore, a so-called jackknife position has to be avoided. In a first step, an initial path is planned from the target to the start configuration using a tree-based path planner. Afterwards this path is refined locally by solving an optimal control problem. Due to the local nature of the planner, heuristic rules for direction changes are formulated. The performance of the proposed path planner is evaluated in simulation studies.

This paper presents a fast optimization based algorithm for car parking. The challenge arises from the non-holonomic characteristics of the car and the close distance to the obstacles. The presented approach utilizes the Minkowski sum to account for obstacle avoidance. The geometric path planning problem is decoupled from the kinematic problem and discretized with respect to the path parameter by means of a Runge-Kutta discretization. For the discrete path segments, an optimization problem is formulated to calculate the path independent of the parking scenario. This static optimization problem can be solved numerically in a very efficient way. The performance of the algorithm is evaluated in several simulation scenarios.