André Rosendo
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CircuitBot: Learning to survive with robotic circuit drawing Open
Robots with the ability to actively acquire power from surroundings will be greatly beneficial for long-term autonomy and to survive in uncertain environments. In this work, a scenario is presented where a robot has limited energy, and the…
PSTO: Learning Energy-Efficient Locomotion for Quadruped Robots Open
Energy efficiency is critical for the locomotion of quadruped robots. However, energy efficiency values found in simulations do not transfer adequately to the real world. To address this issue, we present a novel method, named Policy Searc…
OmniWheg: An Omnidirectional Wheel-Leg Transformable Robot Open
This paper presents the design, analysis, and performance evaluation of an omnidirectional transformable wheel-leg robot called OmniWheg. We design a novel mechanism consisting of a separable omni-wheel and 4-bar linkages, allowing the rob…
Multi-Modal Legged Locomotion Framework with Automated Residual Reinforcement Learning Open
While quadruped robots usually have good stability and load capacity, bipedal robots offer a higher level of flexibility / adaptability to different tasks and environments. A multi-modal legged robot can take the best of both worlds. In th…
Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing Open
Robots with the ability to actively acquire power from surroundings will be greatly beneficial for long-term autonomy and to survive in uncertain environments. In this work, we present a robot capable of drawing circuits with conductive in…
Bootstrapping Virtual Bipedal Walkers with Robotics Scaffolded Learning Open
We reach walking optimality from a very early age by using natural supports, which can be the hands of our parents, chairs, and training wheels, and bootstrap a new knowledge from the recently acquired one. The idea behind bootstrapping is…
Simulating the evolution of bipedalism and the absence of static bipedal hexapods Open
In nature, very few animals locomote on two legs. Static bipedalism can be found in four limbed and five limbed animals like dogs, cats, birds, monkeys and kangaroos, but it cannot be seen in hexapods or other multi-limbed animals. In this…
Risk-Aware Model-Based Control Open
Model-Based Reinforcement Learning (MBRL) algorithms have been shown to have an advantage on data-efficiency, but often overshadowed by state-of-the-art model-free methods in performance, especially when facing high-dimensional and complex…
Scaffolded Learning of In-place Trotting Gait for a Quadruped Robot with Bayesian Optimization Open
During learning trials, systems are exposed to different failure conditions which may break robotic parts before a safe behavior is discovered. Humans contour this problem by grounding their learning to a safer structure/control first and …
Scaffolded Gait Learning of a Quadruped Robot with Bayesian Optimization. Open
During learning trials, systems are exposed to different failure conditions which may break robotic parts before a safe behavior is discovered. Humans contour this problem by grounding their learning to a safer structure/control first and …
A Functional Clipping Approach for Policy Optimization Algorithms Open
Proximal policy optimization (PPO) has yielded state-of-the-art results in policy search, a subfield of reinforcement learning, with one of its key points being the use of a surrogate objective function to restrict the step size at each po…
Proximal Policy Optimization Smoothed Algorithm Open
Proximal policy optimization (PPO) has yielded state-of-the-art results in policy search, a subfield of reinforcement learning, with one of its key points being the use of a surrogate objective function to restrict the step size at each po…
CircuitBot: Learning to Survive with Robotic Circuit Drawing Open
Robots with the ability to actively acquire power from surroundings will be greatly beneficial for long-term autonomy, and to survive in dynamic, uncertain environments. In this work, a scenario is presented where a robot has limited energ…
Scaffolded Learning of Bipedal Walkers: Bootstrapping Ontogenetic Development Open
Bipedal locomotion has several key challenges, such as balancing, foot placement, and gait optimization. We reach optimality from a very early age by using natural supports, such as our parent’s hands, chairs, and training wheels, and boot…
Trade-off on Sim2Real Learning: Real-world Learning Faster than Simulations Open
Deep Reinforcement Learning (DRL) experiments are commonly performed in simulated environments due to the tremendous training sample demands from deep neural networks. In contrast, model-based Bayesian Learning allows a robot to learn good…
Deep vs. Deep Bayesian: Reinforcement Learning on a Multi-Robot Competitive Experiment Open
Deep Reinforcement Learning (RL) experiments are commonly performed in simulated environment, due to the tremendous training sample demand from deep neural networks. However, model-based Deep Bayesian RL, such as Deep PILCO, allows a robot…
Bayesian Reinforcement Learning: Real-world learning faster than simulations. Open
Deep Reinforcement Learning (DRL) experiments are commonly performed in simulated environments due to the tremendous training sample demands from deep neural networks. In contrast, model-based Bayesian learning allows a robot to learn good…
Tactical Reward Shaping: Bypassing Reinforcement Learning with Strategy-Based Goals Open
Deep Reinforcement Learning (DRL) has shown its promising capabilities to learn optimal policies directly from trial and error. However, learning can be hindered if the goal of the learning, defined by the reward function, is "not optimal"…
QR Code-Based Self-Calibration for a Fault-Tolerant Industrial Robot Arm Open
Malfunctions on industrial robots can cost factories 22000 dollars per minute. Although the benefits of a fault-tolerant robot arm are clear, redundant sensors would steeply add to the costs of such robots while machine learning-based meth…
Robotic investigation on effect of stretch reflex and crossed inhibitory response on bipedal hopping Open
To maintain balance during dynamic locomotion, the effects of proprioceptive sensory feedback control (e.g. reflexive control) should not be ignored because of its simple sensation and fast reaction time. Scientists have identified the pat…
Data Fig. 5 and Fig. 6.xlsx Open
This file includes the data of Theta_td and Theta_lo of all the trials (Fig. 5). Also, it contains the comparison of slopes in Fig. 6
supplementary dataset of Robotic Investigation on Effect of Stretch Reflex and Crossed Inhibitory Response on Bipedal Hopping Open
Air Pressure Soleus Fig. 4.xlsx: This file contains the data to describe the air pressure in soleus muscles during stance phaseTheta Fig. 4.xlsx: This file contains the lateral inclination (Theta) during stance phase in hopping.Data Fig.5 …
dataset for the figures (Fig. 4, Fig.5, and Fig.6) Open
Air Pressure Soleus Fig. 4.xlsx: This file contains the data to describe the air pressure in soleus muscles during stance phaseTheta Fig. 4.xlsx: This file contains the lateral inclination (Theta) during stance phase in hopping.Data Fig.5 …
Supplementary material from "Robotic investigation on effect of stretch reflex and crossed inhibitory response on bipedal hopping" Open
To maintain balance during dynamic locomotion, the effects of proprioceptive sensory feedback control (e.g. reflexive control) should not be ignored because of its simple sensation and fast reaction time. Scientists have identified the pat…
supplementary dataset of Robotic Investigation on Effect of Stretch Reflex and Crossed Inhibitory Response on Bipedal Hopping Open
Air Pressure Soleus Fig. 4.xlsx: This file contains the data to describe the air pressure in soleus muscles during stance phaseTheta Fig. 4.xlsx: This file contains the lateral inclination (Theta) during stance phase in hopping.Data Fig.5 …
The trade-off between morphology and control in the co-optimized design of robots Open
Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure …
Evolutionary Developmental Robotics: Improving Morphology and Control of Physical Robots Open
Evolutionary algorithms have previously been applied to the design of morphology and control of robots. The design space for such tasks can be very complex, which can prevent evolution from efficiently discovering fit solutions. In this ar…
Soft Manipulators and Grippers: A Review Open
Soft robotics is a growing area of research which utilizes the compliance and adaptability of soft structures to develop highly adaptive robotics for soft interactions. One area in which soft robotics has the ability to make significant im…