Albert Causo

Analysis and Observations From the First Amazon Picking Challenge

This paper presents an overview of the inaugural Amazon Picking Challenge along with a summary of a survey conducted among the 26 participating teams. The challenge goal was to design an autonomous robot to pick items from a warehouse shelf. This task is currently performed by human workers, and there is hope that robots can someday help increase efficiency and throughput while lowering cost. We report on a 28-question survey posed to the teams to learn about each team’s background, mechanism design, perception apparatus, planning, and control approach. We identify trends in this data, correlate it with each team’s success in the competition, and discuss observations and lessons learned based on survey results and the authors’ personal experiences during the challenge.Note to Practitioners—Perception, motion planning, grasping, and robotic system engineering have reached a level of maturity that makes it possible to explore automating simple warehouse tasks in semistructured environments that involve high-mix, low-volume picking applications. This survey summarizes lessons learned from the first Amazon Picking Challenge, highlighting mechanism design, perception, and motion planning algorithms, as well as software engineering practices that were most successful in solving a simplified order fulfillment task. While the choice of mechanism mostly affects execution speed, the competition demonstrated the systems challenges of robotics and illustrated the importance of combining reactive control with deliberative planning.

Inertia sensor-based guidance system for upperlimb posture correction

Stroke rehabilitation is labor-intensive and time-consuming. To assist patients and therapists alike, we propose a wearable system that measures orientation and corrects arm posture using vibrotactile actuators. The system evaluates user posture with respect to a reference and gives feedback in the form of vibration patterns. Users correct their arm posture, one DOF at a time, by following a protocol starting from the shoulder up to the forearm. Five users evaluated the proposed system by replicating ten different postures. Experimental results demonstrated system robustness and showed that some postures were easier to mimic depending on their naturalness.

Design of Robots Used as Education Companion and Tutor

Robot has a special appeal in education as it can enhance interaction between content-user like students, content-producer like teachers, and the actual material content. Deciding on the form of the robot to use in exploring, testing and implementing educational ideas can be challenging for researchers and educators since form and function could affect user-interaction and determine implementation success. This paper presents a review of published works on robots used in education. Robot design is analyzed with special focus on form, actuation and mobility, interaction capability, and sensing. Robots are grouped into three categories based on the forms they take: humanoid, semi-humanoid, and pet-like.

Automated fish fry counting and schooling behavior analysis using computer vision

This paper presents an automated fish fry counting by detecting the pixel area occupied by each fish silhouette using image processing. A photo of the fish fry in a specially designed container undergoes binarization and edge detection. For every image frame, the total fish count is the sum of the area inside every contour. Then the average number of fishes for every frame is summed up. Experimental data shows that the accuracy rate of the method reaches above 95 percent for a school of 200, 400, 500, and 700 fish fry. To minimize errors due to crowding in the container, schooling behavior analysis is considered. The behavioral effects of different colored lights on milkfish and tilapia are thoroughly investigated. The systems effectiveness, efficiency, possible improvements, and other potential applications are discussed.

Strategies in vibrotactile feedback for improved upper arm posture mapping and replication using inertia sensors

Posture measurement and correction using inertia sensors are finding applications in rehabilitation as well as in human robot interaction systems. This paper presents two designs of arm posture mapping and replication system using inertia sensors and vibrotactile feedback device. The designs differ in the number of vibrotactile actuators and the vibration feedback pattern used. User performance in replicating arm postures when using the different systems were compared. Results show that using fewer vibrotactile actuators to provide feedback is feasible and that a more informative vibration feedback pattern could improve user response time in replicating reference arm postures.

Portable Posture Guiding System With Visual, Verbal Feedback for Upper Extremity

A portable motion replication system for posture guidance of upper extremity is presented in this paper. The system can capture user’s postures, compare the postures with corresponding ones in database, and give the user proper visual and verbal feedback for posture modifying in real time. The experiment of user test shows that the subjects under both visual and verbal feedback have better performance.

Deploying social robots as teaching aid in pre-school K2 classes: A proof-of-concept study

This paper describes the outcome of a pilot study of deploying humanoid social robots as a teaching aid in preschool classroom. Sixteen K2 students each from two pre-schools were recruited to test commercially available robots, Pepper and Nao. The robots were assigned to different schools and were programmed to deliver 6 lessons over a span of 3 months. To assess the deployment and the performance of the children, we used Likert-scale based survey to record our observations. One of the survey forms used was TEPI, which measures the performance of the childrens behavior based on three major criteria. The TEPI data gathered suggests that during the lessons children display desirable behavior such as critical thinking, imagination and creativity, and social interaction and independence. We also observed classroom atmosphere, classroom management, and class behavior during the lessons. Data from the survey highlights the potential benefits and the challenges of deploying robots as a teaching aid in a real classroom setting.

Strategy-based robotic item picking from shelves

Automating item picking in the e-commerce warehouse is pressing but challenging, due to a massive variety of items, tight environmental constraints and item location uncertainty. In this paper, we present an effective and efficient strategy-based planning approach to implement the robotic picking from shelves for e-commerce. Making full advantage of a gripper with multiple securing methods, differentiated strategies are modeled as picking primitives with different securing methods. A strategy generator is proposed to produce feasible potential pickings as quickly and as successfully as possible. A strategy evaluator considering reachability, collision, object-bias preference and the securing performance is also presented for ranking the picking strategies. Experiments were conducted to validate that the robotic picker is able to plan a picking strategy within 2 ms and pick daily items from the shelves with an average success rate of 68%.

Developing and benchmarking show & tell robotic puppet for preschool education

Robots have been shown to assist in education and development of social skills in children. However, there has been no study yet that benchmarks the effectiveness of robots with respect to traditional playtools found inside a classroom, such as pretend play items and blocks. This paper presents the design, development and testing of robotic puppets, which would be used to support teaching in kindergarten education. Different types of robotic puppet design were considered before settling on a glove-type puppet. To benchmark the robot performance, a total of 52 five year-old children were observed, from which quantitative and qualitative data were collected. The result of the study indicates that when playing with the robotic puppets, the performance of the children with respect to thinking and learning, creativity and imagination, and social interaction and independence, is comparable to other traditional playtools.

Measurement of Arm and Hand Motion in Performing Activities of Daily Living (ADL) of Healthy and Post-Stroke Subjects—Preliminary Results

This paper presents an ADL measurement system composed of a measurement table, upper limb measurement system that uses IMU sensors, hand measurement system that uses OLE-based sensor (SmartGlove), and a software system that integrates the sensors and record motion data. Some preliminary data are shown, comparing the motion of a healthy subject to a post-stroke patient’s motion.