We present a new open-source torque-controlled legged robot system, with a low-cost and low-complexity actuator module at its core. It consists of a high-torque brushless DC motor and a low-gear-ratio transmission suitable for impedance and force control. We also present a novel foot contact sensor suitable for legged locomotion with hard impacts. A 2.2 kg quadruped robot with a large range of motion is assembled from eight identical actuator modules and four lower legs with foot contact sensors. Leveraging standard plastic 3D printing and off-the-shelf parts results in a lightweight and inexpensive robot, allowing for rapid distribution and duplication within the research community. We systematically characterize the achieved impedance at the foot in both static and dynamic scenarios, and measure a maximum dimensionless leg stiffness of 10.8 without active damping, which is comparable to the leg stiffness of a running human. Finally, to demonstrate the capabilities of the quadruped, we present a novel controller which combines feedforward contact forces computed from a kino-dynamic optimizer with impedance control of the center of mass and base orientation. The controller can regulate complex motions while being robust to environmental uncertainty.

An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research

Multi-environment robotic transitions through adaptive morphogenesis

Numerous mobile robots in various forms specialize in either ground or aerial locomotion, whereas very few robots can perform complex locomotion tasks beyond simple walking and flying. We present t...

A bipedal walking robot that can fly, slackline, and skateboard.

This paper presents the design and implementation of a bounding controller for the MIT Cheetah 2 and its experimental results. The paper introduces the architecture of the controller along with the...

High-speed bounding with the MIT Cheetah 2: Control design and experiments

HomeRobot (noun): An affordable compliant robot that navigates homes and manipulates a wide range of objects in order to complete everyday tasks. Open-Vocabulary Mobile Manipulation (OVMM) is the problem of picking any object in any unseen environment, and placing it in a commanded location. This is a foundational challenge for robots to be useful assistants in human environments, because it involves tackling sub-problems from across robotics: perception, language understanding, navigation, and manipulation are all essential to OVMM. In addition, integration of the solutions to these sub-problems poses its own substantial challenges. To drive research in this area, we introduce the HomeRobot OVMM benchmark, where an agent navigates household environments to grasp novel objects and place them on target receptacles. HomeRobot has two components: a simulation component, which uses a large and diverse curated object set in new, high-quality multi-room home environments; and a real-world component, providing a software stack for the low-cost Hello Robot Stretch to encourage replication of real-world experiments across labs. We implement both reinforcement learning and heuristic (model-based) baselines and show evidence of sim-to-real transfer. Our baselines achieve a 20% success rate in the real world; our experiments identify ways future research work improve performance. See videos on our website: https://ovmm.github.io/.

pdf/homerobot-open-vocabulary-mobile-manipulation-34ndiwx2.pdf

HomeRobot: Open-Vocabulary Mobile Manipulation

This paper presents Stanford Doggo, a quasi-direct-drive quadruped capable of dynamic locomotion. This robot matches or exceeds common performance metrics of state-of-the-art legged robots. In terms of vertical jumping agility, a measure of average vertical speed, Stanford Doggo matches the best performing animal and surpasses the previous best robot by 22%. An overall design architecture is presented with focus on our quasi-direct-drive design methodology. The hardware and software to replicate this robot is open-source, requires only hand tools for manufacturing and assembly, and costs less than $3000.

Stanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped

The current process of undertaking, implementing, reviewing, and finally publishing a scientific study is riddled with flaws, as the study results are subjected to many biases and interpretations at every level between instigation and publication. As a result, when these studies finally reach the public, they are often depicted in ways that don’t parallel the genuine results, and are at times utterly incorrect. Industries touting their products, scientists influenced by grants and prestige, reviewers adhering to personal political agendas, and journalists pressed to sell papers, all in turn contribute to the inherently skewed depiction of scientific results to the public. These factors have allowed for a highly unpredictable credibility in scientific reporting, an observation that has been highly overlooked and disregarded. The dissemination and publicity of this incorrect or skewed information, which is believed to be scientifically accurate, can have a detrimental affect on the public in their everyday lives.

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The Dubious Credibility of Scientific Studies

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Stanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped

Stanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped

The Dubious Credibility of Scientific Studies