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Energy Efficient Multi Robot Package Delivery under Capacity-Constraints via Voronoi-Constrained Networks

Srivastava, Alkesh K., Levin, Jared Michael, Dames, Philip

arXiv.org Artificial Intelligence

We consider the problem of delivering multiple packages from a single pickup depot to distinct goal locations using a homogeneous fleet of robots with limited carrying capacity. We propose VCST-RCP, a Voronoi-Constrained Steiner Tree Relay Coordination Planning framework that constructs sparse relay trunks using Steiner tree optimization and then synthesizes robot-level pickup, relay, and delivery schedules. This framework reframes relays from incidental byproducts into central elements of coordination, offering a contrast with traditional delivery methods that rely on direct source-to-destination transport. Extensive experiments show consistent improvements of up to 34% compared to conventional baselines, underscoring the benefits of incorporating relays into the delivery process. These improvements translate directly to enhanced energy efficiency in multi-robot delivery under capacity constraints, providing a scalable framework for real-world logistics.


Design Method of a Kangaroo Robot with High Power Legs and an Articulated Soft Tail

Yoshimura, Shunnosuke, Suzuki, Temma, Bando, Masahiro, Yuzaki, Sota, Kawaharazuka, Kento, Okada, Kei, Inaba, Masayuki

arXiv.org Artificial Intelligence

In this paper, we focus on the kangaroo, which has powerful legs capable of jumping and a soft and strong tail. To incorporate these unique structure into a robot for utilization, we propose a design method that takes into account both the feasibility as a robot and the kangaroo-mimetic structure. Based on the kangaroo's musculoskeletal structure, we determine the structure of the robot that enables it to jump by analyzing the muscle arrangement and prior verification in simulation. Also, to realize a tail capable of body support, we use an articulated, elastic structure as a tail. In order to achieve both softness and high power output, the robot is driven by a direct-drive, high-power wire-winding mechanism, and weight of legs and the tail is reduced by placing motors in the torso. The developed kangaroo robot can jump with its hind legs, moving its tail, and supporting its body using its hind legs and tail.


Design Optimization of Wire Arrangement with Variable Relay Points in Numerical Simulation for Tendon-driven Robots

Kawaharazuka, Kento, Yoshimura, Shunnosuke, Suzuki, Temma, Okada, Kei, Inaba, Masayuki

arXiv.org Artificial Intelligence

One of the most important features of tendon-driven robots is the ease of wire arrangement and the degree of freedom it affords, enabling the construction of a body that satisfies the desired characteristics by modifying the wire arrangement. Various wire arrangement optimization methods have been proposed, but they have simplified the configuration by assuming that the moment arm of wires to joints are constant, or by disregarding wire arrangements that span multiple joints and include relay points. In this study, we formulate a more flexible wire arrangement optimization problem in which each wire is represented by a start point, multiple relay points, and an end point, and achieve the desired physical performance based on black-box optimization. We consider a multi-objective optimization which simultaneously takes into account both the feasible operational force space and velocity space, and discuss the optimization results obtained from various configurations.


A Generalization of Sleep Sets Based on Operator Sequence Redundancy

Holte, Robert C. (University of Alberta) | Alkhazraji, Yusra (University of Freiburg) | Wehrle, Martin (University of Basel)

AAAI Conferences

Pruning techniques have recently been shown to speed up search algorithms by reducing the branching factor of large search spaces. One such technique is sleep sets, which were originally introduced as a pruning technique for model checking, and which have recently been investigated on a theoretical level for planning. In this paper, we propose a generalization of sleep sets and prove its correctness. While the original sleep sets were based on the commutativity of operators, generalized sleep sets are based on a more general notion of operator sequence redundancy. As a result, our approach dominates the original sleep sets variant in terms of pruning power. On a practical level, our experimental evaluation shows the potential of sleep sets and their generalizations on a large and common set of planning benchmarks.