29 citations · 53 across the 11 of their papers we have counts for
11 papers
BLISS: Interplanetary Exploration with Swarms of Low-Cost Spacecraft
Alexander N. Alvara, Lydia Lee, Emmanuel Sin +3
Leveraging advancements in micro-scale technology, we propose a fleet of autonomous, low-cost, small solar sails for interplanetary exploration. The Berkeley Low-cost Interplanetar…
Investigating Compounding Prediction Errors in Learned Dynamics Models
Nathan Lambert, Kristofer Pister, Roberto Calandra
Accurately predicting the consequences of agents' actions is a key prerequisite for planning in robotic control. Model-based reinforcement learning (MBRL) is one paradigm which rel…
BotNet: A Simulator for Studying the Effects of Accurate Communication Models on Multi-agent and Swarm Control
Mark Selden, Jason Zhou, Felipe Campos +3
Decentralized control in multi-robot systems is dependent on accurate and reliable communication between agents. Important communication factors, such as latency and packet deliver…
Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning
Nathan O. Lambert, Albert Wilcox, Howard Zhang +2
Accurately predicting the dynamics of robotic systems is crucial for model-based control and reinforcement learning. The most common way to estimate dynamics is by fitting a one-st…
Nonholonomic Yaw Control of an Underactuated Flying Robot with Model-based Reinforcement Learning
Nathan Lambert, Craig Schindler, Daniel Drew +1
Nonholonomic control is a candidate to control nonlinear systems with path-dependant states. We investigate an underactuated flying micro-aerial-vehicle, the ionocraft, that requir…
Learning for Microrobot Exploration: Model-based Locomotion, Sparse-robust Navigation, and Low-power Deep Classification
Nathan O. Lambert, Farhan Toddywala, Brian Liao +3
Building intelligent autonomous systems at any scale is challenging. The sensing and computation constraints of a microrobot platform make the problems harder. We present improveme…
Data-efficient Learning of Morphology and Controller for a Microrobot
Thomas Liao, Grant Wang, Brian Yang +4
Robot design is often a slow and difficult process requiring the iterative construction and testing of prototypes, with the goal of sequentially optimizing the design. For most rob…
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning
Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli +3
Designing effective low-level robot controllers often entail platform-specific implementations that require manual heuristic parameter tuning, significant system knowledge, or long…
Decentralized Control of a Hexapod Robot Using a Wireless Time Synchronized Network
James Fang, Dinesh Parimi, Arjun Dhindsa +2
Robots and control systems rely upon precise timing of sensors and actuators in order to operate intelligently. We present a functioning hexapod robot that walks with a dual tripod…
Learning Flexible and Reusable Locomotion Primitives for a Microrobot
Brian Yang, Grant Wang, Roberto Calandra +3
The design of gaits for robot locomotion can be a daunting process which requires significant expert knowledge and engineering. This process is even more challenging for robots tha…
New Directions: Wireless Robotic Materials
Nikolaus Correll, Prabal Dutta, Richard Han +1
We describe opportunities and challenges with wireless robotic materials. Robotic materials are multi-functional composites that tightly integrate sensing, actuation, computation a…