Multi-Contact Grasp Interaction for Virtual Environments

The grasping of virtual objects has been an active research field for several years. Solutions providing realistic grasping rely on special hardware or require time-consuming parameterizations. Therefore, we introduce a flexible grasping algorithm enabling grasping without computational complex physics. Objects can be grasped and manipulated with multiple fingers. In addition, multiple objects can be manipulated simultaneously with our approach. Through the usage of contact sensors the technique is easily configurable and versatile enough to be used in different scenarios.

GRASP with Hybrid Path Relinking for Bi-Objective Winner Determination in Combinatorial Transportation Auctions

The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper's task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm.