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Giorgio Valsecchi

7 accepted papers

2025

LEVA: A High-Mobility Logistic Vehicle with Legged Suspension

ICRA 2025

The autonomous transportation of materials over challenging terrain is a challenge with major economic implications and remains unsolved. This paper introduces LEVA, a high-payload, high-mobility robot designed for autonomous logistics across varied terrains, including those typical in agriculture,

Cited by 5SourceScholar
2024

Accurate power consumption estimation method makes walking robots energy efficient and quiet

IROS 2024

Power consumption is a frequently over-looked aspect in robotics, especially in the context of legged robots. Nevertheless, improving the efficiency of walking robots is crucial to overcome the current limitations in runtime. This work proposes a novel method for precisely estimating actuator power

Cited by 4SourceScholar
2023

Barry: A High-Payload and Agile Quadruped Robot

RA-L 2023

This letter introduces Barry, a dynamically balancing quadruped robot optimized for high payload capabilities and efficiency. It presents a new high-torque and low-inertia leg design, which includes custom-built high-efficiency actuators and transparent, sensorless transmissions. The robot's reinfor

Cited by 23SourceScholar
2023

Towards Legged Locomotion on Steep Planetary Terrain

IROS 2023poster

Scientific exploration of planetary bodies is an activity well-suited for robots. Unfortunately, the regions that are richer in potential discoveries, such as impact craters, caves, and volcanic terraces, are hard to access with wheeled robots. Recent advances in legged-based approaches have shown t…

Cited by 11SourceScholar
2022

Design and Motion Planning for a Reconfigurable Robotic Base

RA-L 2022

A robotic platform for mobile manipulation needs to satisfy two contradicting requirements for many real-world applications: A compact base is required to navigate through cluttered indoor environments, while the support needs to be large enough to prevent tumbling or tip over, especially during fas

Cited by 10SourcecodeScholar
2022

Meta Reinforcement Learning for Optimal Design of Legged Robots

RA-L 2022

The process of robot design is a complex task and the majority of design decisions are still based on human intuition or tedious manual tuning. A more informed way of facing this task is computational design methods where design parameters are concurrently optimized with corresponding controllers. E

Cited by 43SourceScholar